Multidimensional Research Articles

Multi-Dimensional Medical Image Fusion With Complex Sparse Representation.

In the field of medical imaging, the fusion of data from diverse modalities plays a pivotal role in advancing our understanding of pathological conditions. Sparse representation (SR), a robust signal modeling technique, has demonstrated noteworthy success in multi-dimensional (MD) medical image fusion. However, a fundamental limitation appearing in existing SR models is their lack of directionality, restricting their efficacy in extracting anatomical details from different imaging modalities. To tackle this issue, we propose a novel directional SR model, termed complex sparse representation (ComSR), specifically designed for medical image fusion. ComSR independently represents MD signals over directional dictionaries along specific directions, allowing precise analysis of intricate details of MD signals. Besides, current studies in medical image fusion mostly concentrate on addressing either 2D or 3D fusion problems. This work bridges this gap by proposing a MD medical image fusion method based on ComSR, presenting a unified framework for both 2D and 3D fusion tasks. Experimental results across six multi-modal medical image fusion tasks, involving 93 pairs of 2D source images and 20 pairs of 3D source images, substantiate the superiority of our proposed method over 11 state-of-the-art 2D fusion methods and 4 representative 3D fusion methods, in terms of both visual quality and objective evaluation. The source code of our fusion method is available at https://github.com/Imagefusions/imagefusions/tree/main.

A corpus-based multi-dimensional analysis of the linguistic features of Aviation English

Aviation English (AE), a specialized register of English, prioritizes precision, brevity and clarity to maximize aviation safety. While there has been a growing focus within the linguistics community on AE training and assessment since the release of a set of standards and recommended practices, its linguistic properties remain comparatively underexplored. Drawing upon Biber's (1988) multi-dimensional (MD) analysis framework, the present study conducted a corpus-based comparative MD analysis to investigate the multi-dimensional linguistic profile of AE vs. casual conversational English (CE) and exploratory factor analysis (EFA) to extract and interpret the co-occurring linguistic features of routine AE and non-routine AE. The comparative MD analysis shows that AE exhibits more information condensation, less authorial stance and technicality, and fewer features of online information elaboration compared to CE. The EFA shows variations in the linguistic and textual composition of the two sub-registers of AE across two dimensions. Non-routine AE demonstrates a present-focused, viewpoint/intention-oriented approach, involving higher levels of integrative information flow compared to routine AE. Routine AE is characterized by a higher degree of information condensation and is marked by a planned, procedural, and intensive use of standard phraseology. Some pedagogical implications are then proposed for enhancing AE training to cultivate pilots' and air traffic controllers' language competence for precise, unambiguous communication tailored to both routine and non-routine operational contexts.

Linguistic variation in two written academic sub-registers

Abstract The present study aims to compare abstracts written by graduate students and internationally-published authors using Biber’s (1988) Multi-Dimensional (MD) model. To this end, two corpora of abstracts (1800 texts each) from research articles (RA) published in top international Applied Linguistics journals, and theses completed in the same field were compiled. We compared the two corpora with regard to three of Biber’s (1988) dimensions: involved versus informational production; elaborated vs. situation-dependent reference; and abstract vs. non-abstract style. Our results revealed that RA abstracts and thesis abstracts are similar when compared to non-academic registers of English, but different when compared to each other. Relative to thesis abstracts, RA abstracts are more informational but less elaborated and less impersonal. Interestingly, we found that RA/thesis abstracts differ from Biber’s (1988) academic prose register along the three dimensions. Our findings can further our understanding of the differences between RA and thesis abstracts, thus contributing to the instruction of academic writing at the graduate level.

A Multi-Dimensional Calibration Based on Genetic Algorithm in a 12-Bit 750 MS/s Pipelined ADC.

As the preferred architecture for high-speed and high-resolution analog-to-digital converters (ADC), the accuracy of pipelined ADC is limited mainly by various errors arising from multiple digital-to-analog converters (MDAC). This paper presents a multi-dimensional (M-D) MDAC calibration based on a genetic algorithm (GA) in a 12-bit 750 MS/s pipelined ADC. The proposed M-D MDAC compensation model enables capacitor mismatch and static interstage gain error (IGE) compensation on the chip and prepares for subsequent background calibration based on a pseudo-random number (PN) injection to achieve accurate compensation for dynamic IGE. An M-D coefficient extraction scheme based on GA is also proposed to extract the required compensation coefficients of the foreground calibration, which avoids falling into local traps through MATLAB. The above calibration scheme has been verified in a prototype 12-bit 750 MS/s pipelined ADC. The measurement results show that the signal-to-noise and distortion ratio (SNDR) and spurious-free dynamic range (SFDR) are increased from 49.9 dB/66.7 dB to 59.6 dB/77.5 dB with the proposed calibration at 25 °C. With the help of background calibration at 85 °C, the SNDR and SFDR are improved by 3.4 dB and 8.8 dB, respectively.

A New Integrated Model for Simulating Adaptive Cycle Engine Performance Considering Variations in Tip Clearance

The low-fidelity simulation method cannot meet the requirements for predicting the performance of an adaptive cycle engine (ACE), especially when considering tip clearance variations in the compression and expansion systems. The tip clearances of the components of an ACE, such as the adaptive fan and turbine, vary drastically under different operating conditions. Though the tip clearance significantly impacts the engine’s performance, including its thrust and fuel consumption, variations in tip clearance are not considered in traditional ACE simulation models. This paper developed a new integrated model for predicting ACE performance, including multi-fidelity simulation models of the components and a newly developed, simplified model for predicting tip clearance. Specifically, the integrated model consists of a zero-dimensional (0D) engine performance simulation model, a three-dimensional (3D) adaptive fan numerical simulation model, a one-dimensional (1D) low-pressure-turbine (LPT) mean line model, and a multi-dimensional (MD) tip clearance prediction model. The integrated model solved the problem of considering the impact of tip clearance on an ACE and further improved the accuracy of thrust and fuel consumption predictions. Specifically, considering variations in the tip clearances under the design conditions, the differences in the thrust and specific fuel consumption (SFC) of the ACE are 1% and 0.3%, respectively. In conclusion, the integrated model provides a useful tool for evaluating the performance of an ACE while considering tip clearance variations.

An n-dimensional modulo chaotic system with expected Lyapunov exponents and its application in image encryption

One-dimensional (1D) chaotic maps have many shortcomings, including simple structures, uncomplicated chaotic behaviors, and narrow chaotic ranges. Multi-dimensional (MD) chaotic maps certainly have more complex constructions and more abundant chaotic phenomena. However, it is still challenging to artificially customize its Lyapunov exponents (LEs), which are characterization indicators of the chaotic state. This paper proposed a novel n-dimensional (nD) modulo chaotic system (nD-MCS) based on preceding works that can generate nD chaotic maps by using existing 1D chaotic maps as seed chaotic maps. The proposed nD-MCS can customize its LEs by setting system parameters. Three 2D and three 3D chaotic maps are presented as examples. Performance evaluations demonstrated that they both exhibit hyperchaotic behaviors, broad chaotic ranges, and large complexities. We present an encryption scheme to confirm the application of the developed chaotic maps to image encryption. Finally, a hardware experiment utilizing the field-programmable gate array (FPGA) is adapted to verify the proposed cryptosystem.

A Multidimensional Analysis of Language Use in English Argumentative Essays: An Evidence From Comparable Corpora

Multidimensional (MD) analysis contributes to a comprehensive linguistic description of second language (L2) writing texts. However, cross-linguistic studies based on MD analysis are still insufficient and need to be increased. In particular, the unavailability of comparable corpora prevents current MD-based L2 writing research from making reliable comparisons of linguistic differences between native writers and L2 learners. Considering these, this study adopts corpora of maximum similarity for the cross-linguistic comparative analysis. Using Biber’s MD analysis, this study compares linguistic differences between native English writers and Chinese English learners in argumentative essays with similar communicative purposes. The analysis reveals that the two groups of texts show significant differences in slightly over half of the individual linguistic features but share more similarities than differences in textual dimensions. It also shows that the two groups are, in fact, different varieties of English language use, even though they share a similar text type of “involved persuasion.” The results confirm the importance of comparable corpora for cross-linguistic comparisons and the necessity of MD analysis for understanding L2 writing.

A corpus-based analysis of the stylistic features of Chinese and American diplomatic discourse.

The study investigates the linguistic aspects of Chinese and American diplomatic discourse using Biber's theoretical underpinnings of multi-dimensional (MD) analysis. The corpus of the study comprises texts taken from the official websites of the Chinese and US governments from 2011 to 2020. The study results show that China's diplomatic discourse falls into the text type of learned exposition which includes informational expositions focused on conveying information. In contrast, the United States diplomatic discourse falls into the text type of "involved persuasion," which is persuasive and argumentative. Furthermore, the two-way ANOVA test reveals few distinctions between spoken and written diplomatic discourse from the same country. Furthermore, T-tests demonstrate that the diplomatic discourse of the two countries differs significantly in three dimensions. In addition, the study highlights that China's diplomatic discourse is informationally dense and context independent. In contrast, the United States diplomatic discourse is emotive and interactional, strongly dependent on context, and created within time restrictions. Finally, the study's findings contribute to a systematic knowledge of the genre aspects of diplomatic discourse and are helpful for more effective diplomatic discourse system creation.

Geometrically-Shaped Multi-Dimensional Modulation Formats in Coherent Optical Transmission Systems

Shaping modulation formats in multi-dimensional (MD) space is an effective approach to harvest spectral efficiency gains in both the additive white Gaussian noise (AWGN) channel and the optical fiber channel. In the first part of this paper, existing MD geometrically-shaped modulations for fiber optical communications are reviewed. It is shown that large gains can be obtained by exploiting correlation in the dimensions or/and by increasing the cardinality of the modulation format. Practical limitations and challenges are also discussed together with efficient solutions. In the second part, we extend the recently proposed four-dimensional (4D) modulation format family based on the constraint of orthant-symmetry to high spectrum efficiencies up to 10 b/4D-sym by maximizing generalized mutual information for AWGN channel. Reach increases of up to 25% for a multi-span optical fiber transmission system are reported. Lastly, with the help of a recently introduced nonlinear interference (NLI) model, an optimization for designing nonlinear-tolerant 4D modulation formats is introduced for a single-span optical fiber system. Simulation results show that the proposed NLI model-based 4D modulation format could increase the effective SNRs by 0.25 dB with respect to the AWGN channel-optimal 4D modulation format.

Multidimensional spectroscopy of heavy impurities in ultracold fermions

We investigate the system of a heavy impurity immersed in a degenerate Fermi gas, where the impurity's internal degree of freedom (pseudospin) is manipulated by a series of radio-frequency (RF) pulses at several different times. Applying the functional determinant approach, we carry out an essentially exact calculation of the Ramsey-interference-type responses to the RF pulses. These responses can be regarded as multidimensional (MD) spectroscopy of the system in the time domain. Similar to their one-dimensional counterpart studied by Knap et al. [M. Knap et al., Phys. Rev. X 2, 041020 (2012)], these responses are universal functions. A Fourier transformation of the time intervals gives the MD spectroscopy in the frequency domain, providing insightful information on the many-body correlation and relaxation via the cross peaks, e.g., the off-diagonal peaks in a two-dimensional spectrum. These features are inaccessible for the conventional, one-dimensional absorption spectrum. Our scheme provides a different method to investigate many-body nonequilibrium physics beyond the linear response regime with accessible tools in cold atoms.

A Multi-Dimensional Analysis of English Writings by Chinese EFL Learners

The exponential growth in the population of Chinese EFL learners has fueled the study of Chinese EFL learner writing. A survey of relevant literature indicates that the majority of studies are confined to the exploration of individual linguistic features, with a few exceptions which employ a broader perspective that might involve multiple features. This work aims to investigate the English writings by Chinese EFL learners via Multi-Dimensional (MD) analysis, a corpus-based approach that combines both microscopic (i.e., individual linguistic features) and macroscopic perspectives (i.e., textual dimensions). A comparison between writings by Chinese EFL learners and native English speakers shows that the former are high on involvement, informativeness, and referential explicitness while the latter exhibit superiority on word-choosing, information integration, narrativity, and persuasiveness. Regarding their specific use of 67 MD linguistic features, the two writer groups also show certain significant but interesting differences. Analysis of Chinese EFL learner corpora from different English education levels indicates that writings by learners from higher levels are lower on involvement, but are higher on informativeness, narrativity, referential explicitness, and persuasiveness. This trend is manifested by their decreasing use of involvement features, but increasing use of features marking the latter four aspects.

A novel image encryption algorithm based on hybrid chaotic maps using a key image

One of the most important data currently shared on the Internet is images of various sizes and types, gray and color, private and public, civilian and military, medical and scientific, commercial, and others. The biggest challenge and problem is the secure transmission of these images in this insecure environment. In this context, this paper proposes a new image encryption algorithm using a hybrid of three modified and improved chaotic one-dimensional (1D) maps to avoid the shortcomings of 1D maps and multidimensional (MD) maps. A key image is used to initialize the chaotic maps and is also used as a mask in the diffusion phase with the eXclusive OR (XOR) operator. The encryption process uses ExtraParam extracted from the original image, which is very sensitive to bit changes during the initialization of the chaotic maps. The proposed encryption process consists of two main phases: confusion and diffusion processes. The proposed image encryption algorithm has successfully passed numerous tests and cryptanalysis. We also measure the proposed algorithm with various analysis experiments such as histogram and entropy analysis, the number of pixel change rate (NPCR), the unified average changing intensity (UACI), the mean square error(MSE), the peak signal-to-noise ratio (PSNR) and Key Space. The experimental results and comparative analysis show that the proposed encryption algorithm has excellent performance, is strong enough to withstand various attacks, and provides excellent privacy to digital images.

Phase rearrangement shell mapping in single-span nonlinear optical fiber communication system

The importance of single-span systems is emphasized by the fact that they currently constitute the fastest growing section of the fiber communication markets. In such systems, the correlation time of the nonlinear phase noise is too short to allow the nonlinear phase-noise mitigation such as adaptive phase-recovery or equalization, while it is sufficient for the shaping approaches. The multi-dimensional (MD) coded-modulation based standard shell mapping (SM) algorithm can realize signal shaping and mitigate the nonlinear phase noise in single-span optical fiber transmissions. However, the standard SM algorithm has poor performance resulted from the decoding penalty in two-dimensional (2D) decoding with a low signal-to-noise (SNR) ratio. In this paper, we propose a phase rearrangement shell mapping (PRSM) algorithm to improve the 2D decoding performance by rearranging the constellation sequence in order of signal phase for each shell. This proposed technique is verified through the simulation of a 5 × 70-GBaud 4D/8D modulated signal in a 5-channel wavelength division multiplexing (WDM) system after a single span transmission of 100-km standard single mode fiber (SSMF). We also conduct an experiment to verify the performance of 3 × 45-GBaud 4D/8D-16QAM with PRSM algorithm after unrepeated transmission of 100-km SSMF. The simulation and experimental results show that the Q2 factor gain of PRSM-4D/8D-16QAM is about 0.2∼0.3 dB compared with standard SM-4D/8D-16QAM using 2D decoding. There is about 1.6-dB or 1.8-dB launch optical power (LOP) dynamic range improvement by PRSM compared with standard SM for 4D/8D-16QAM, respectively.

3D inverse synthetic aperture radar image quality improvement using sparse signal representation

AbstractGeneralisation of one‐dimensional dictionary learning (1DDL) algorithms to Multidimensional (MD) mode and its utilisation in MD data applications, increases the speed and reduces the computational complexity. An example of such an application is 3D inverse synthetic aperture radar (ISAR) image reconstruction and noise reduction. In this study, in addition to MD mode generalisation, the formulation structure of the multidimensional dictionary learning (MDDL) problem is discussed followed by two novel algorithms to solve it. The first one is based on the K‐singular value decomposition algorithm for 1DDL, which uses alternating minimisation and singular value decomposition. The second algorithm is the extension of the sequential generalisation of K‐means 1DDL algorithm to the MD mode. Moreover, the MD tensor denoising method based on the MDDL algorithm (MDDL‐ALG) is proposed. As an application, the proposed method is used to denoise the 3D ISAR image. The numerical simulations reveal that the proposed methods, in addition to reducing the memory consumption and the computational complexity, also enjoy higher convergence rate in comparison to 1D algorithms. Specifically, convergence speed of MD algorithms, depending on the training data size, is up to at least 10 times faster than the equivalent 1D counterparts. As revealed through the simulations, the amount of signal to noise ratio recovered by the proposed methods is almost 2 dB higher than the case using a pre‐designed dictionary for denoising. Moreover, it outperforms about 10 dB over the case with the conventional 3D‐IFFT method for image construction.

A text typology of social media

Abstract This paper introduces an initial text typology of social media posts from a multi-dimensional (MD) perspective. Text types are “[g]roupings of text that are similar in their linguistic form” (Biber 1989: 13). This text typology is based on a new MD analysis of social media messages presented in the paper. The corpus consists of 60,000 social media messages in English compiled from Facebook, Twitter, Instagram, Reddit, Telegram, and YouTube. After the texts were cleaned up, the corpus was tagged with the Biber Tagger and post-processed with the Biber Tag Count. Three dimensions of variation were determined, each representing an underlying parameter of variation. Once the texts were scored on each of the dimensions, a k-means cluster analysis was carried out, and the optimal number of clusters was determined using the Cubic Clustering Criterion statistic. A two-way typology was developed based on the dimensional characteristics of each cluster and on careful qualitative analysis of text samples.

Designing Enhanced Multidimensional Constellations for Code-Domain NOMA

This letter presents an enhanced design of multi-dimensional (MD) constellations which play a pivotal role in many communication systems such as code-domain non-orthogonal multiple access (CD-NOMA). MD constellations are attractive as their structural properties, if properly designed, lead to signal space diversity and hence improved error rate performance. Unlike the existing works which mostly focus on MD constellations with large minimum Euclidean distance (MED), we look for new MD constellations with additional feature that the minimum product distance (MPD) is also large. To this end, a non-convex optimization problem is formulated and then solved by the convex-concave procedure (CCCP). Compared with the state-of-the-art literature, our proposed MD constellations lead to significant error performance enhancement over Rayleigh fading channels whilst maintaining almost the same performance over the Gaussian channels. To demonstrate their application, we also show that these MD constellations give rise to good codebooks in sparse code multiple access systems.

Does change in the scoring system impact service evaluation? Evidence from Booking.com

PurposeIn September 2019, Booking.com changed from the smiley-based scoring system (2.5–10) to the purely 10-point evaluation system (1–10). The smiley-based service evaluation is based on the multi-dimensional (M-D) system, whereas the purely 10-point service evaluation is based on the single-dimensional (S-D) system. This paper aims to focus on how a change in review posting policies impacts service evaluations regarding review generation and distribution.Design/methodology/approachThe authors exploit the natural experiment using Booking.com when the site changed its scoring system from a multidimensional smiley-based service evaluation system to an S-D scoring system. The authors collected online reviews posted on two travel agencies (Booking.com and Priceline.com) between September 2019 and October 2020. A quasi-experimental approach, Difference-in-Differences, was used to isolate the impacts of the new scoring system from the impacts of the change in the service evaluation environment, i.e. COVID-19.FindingsThe change in the scoring system considerably alters review distributions by decreasing the portion of positive reviews but increasing the portion of highly positive reviews. Using the theory of emotion work (Hochschild, 1979, 2001), DID is also the reason that the former M-D smiley-based system could have underrated, highly positive reviews of services. Using the information transfer theory (Belkin, 1984), the authors reason the asymmetric transfer of information when users consume reviews from the older (M-D) system but are required to generate reviews on a newer (S-D) system.Practical implicationsThe findings would provide online review platform management with a deeper understanding of the consequences of changes in service evaluations when the scoring system is changed.Originality/valueThough the change in the scoring system would affect how customers evaluate the services of hotels, the causal impacts of switching to the new S-D scoring system have not yet been thoroughly covered by prior hospitality and service evaluation literature, which this research aspires to do.

Boosting Efficiency of Non‐Fullerene Organic Solar Cells Via Introducing Multidimensional Second Acceptors

The active layer bulk heterojunction (BHJ) blends with a suitable phase separation and crystallization are of great importance to the exciton dissociation, charge transfer, and ultimately the efficiency of the organic solar cells (OSCs). Herein, an effective approach is developed to modulate the molecule's crystallization and phase separation of BHJ blends via introducing a multidimensional (MD) second acceptor. The efficiency of the OSCs can be largely boosted when the cross‐shaped MD acceptors are introduced into the BHJs as a third component. The ternary OSCs based on PTB7‐Th:IEICO‐4F:SFCPDT exhibit a higher power conversion efficiency (PCE) (PCE = 13.29%) than that of the PTB7‐Th:IEICO‐4F binary system (PCE = 11.67%). It is found that the ternary films deliver higher and more balanced carrier mobility, as well as reduced carrier recombination. The positive effect can be also extended to the PBDB‐T‐2F: IT‐4F‐based ternary system. When FLIDT and SFIDT are employed as the third component, the PCE values can be increased from pristine 11.98–12.42% and 13.16%, respectively. It is anticipated to further boost the efficiency of the non‐fullerene OSCs by rationally designing the structure of the third component for a state‐of‐the‐art active layer system.

Fast multidimensional dictionary learning algorithms and their application in 3D inverse synthetic aperture radar image restoration and noise reduction

By generalising dictionary learning (DL) algorithms to multidimensional (MD) mode and using them in applications where signals are inherently multidimensional, such as in three-dimensional (3D) inverse synthetic aperture radar (ISAR) imaging, it is possible to achieve much higher speed and less computational complexity. In this study, the formulation of the multidimensional dictionary learning (MDDL) problem is expressed and two algorithms are proposed to solve it. The first one is based on the method of optimum directions (MOD) algorithm for 1D dictionary learning (1DDL), which uses alternating minimisation and gradient projection approach. As the MDDL problem is non-convex, the second algorithm approximates the non-convex objective with a new jointly convex function and efficiently solves it. As an application, we use the proposed methods to restore and denoise the ISAR image. Numerical experiments highlight that the proposed algorithms, in addition to reducing the computational complexity and the amount of required memory, also entail less training data for learning the dictionary, and enjoy higher convergence speed in comparison to their one-dimensional (1D) counterparts. Specifically, convergence speed of MD algorithms, depending on the size of the training data, is up to at least 10.7 times faster than the equivalent 1DDL algorithm. According to the simulation results, the SNR value achieved by the proposed algorithms is higher than the case where we use the 3D-IFFT for image reconstruction and the case of fixed dictionaries, by approximately 12 and 4 dB, respectively.

Minimax Design of M-D Sparse FIR Filters With Arbitrary Frequency Response Using SOCP

The number of coefficients of multi-dimensional (M-D) finite-extent impulse response (FIR) filters increases exponentially with the number of dimensions leading to significantly high computational complexities. In this brief, we propose a minimax design method for M-D FIR filters having sparse coefficients, therefore, having low computational complexities. We consider the design of M-D FIR filters with arbitrary frequency responses and low group delays of which the coefficients are complex valued. We formulate the minimax design as a second-order cone programming problem. Design examples confirm that M-D sparse FIR filters designed using the proposed method provide more than 60% reduction in the computational complexity for a similar error in the frequency response approximation compared to M-D FIR nonsparse filters designed using previously proposed minimax methods.