Embedded Domains Research Articles

Integrating subsystem embedding subalgebras and coupled cluster Green’s function: a theoretical foundation for quantum embedding in excitation manifold

In this study, we introduce a novel approach to coupled-cluster Green’s function (CCGF) embedding by seamlessly integrating conventional CCGF theory with the state-of-the-art sub-system embedding sub-algebras coupled cluster (SES-CC) formalism. This integration focuses primarily on delineating the characteristics of the sub-system and the corresponding segments of the Green’s function, defined explicitly by active orbitals. Crucially, our work involves the adaptation of the SES-CC paradigm, addressing the left eigenvalue problem through a distinct form of Hamiltonian similarity transformation. This advancement not only facilitates a comprehensive representation of the interaction between the embedded sub-system and its surrounding environment but also paves the way for the quantum mechanical description of multiple embedded domains, particularly by employing the emergent quantum flow algorithms. Our theoretical underpinnings further set the stage for a generalization to multiple embedded sub-systems. This expansion holds significant promise for the exploration and application of non-equilibrium quantum systems, enhancing the understanding of system–environment interactions. In doing so, the research underscores the potential of SES-CC embedding within the realm of quantum computations and multi-scale simulations, promising a good balance between accuracy and computational efficiency.

A lightweight deep learning model for real‐time face recognition

AbstractLightweight deep learning models for face recognition are becoming increasingly crucial for deployment on resource‐constrained devices such as embedded systems or mobile devices. This paper presents a highly efficient and compact deep learning (DL) model that achieves state‐of‐the‐art performance on various face recognition benchmarks. The developed DL model employs one‐ or few‐shot learning to obtain effective feature embeddings and draws inspiration from FaceNet with significant refinements to achieve a memory size of only 3.5 MB—about 30 times smaller than FaceNet—while maintaining high accuracy and real‐time performance. The study demonstrates the model's effectiveness through extensive experiments, which include testing on public datasets and the model's ability to recognize occluded faces in uncontrolled environments using grayscale input images. Compared to the state‐of‐the‐art lightweight models, the proposed model requires fewer FLOPs (0.06G), has a smaller number of parameters (1.2 M), and occupies a smaller model size (3.5 MB) while achieving a competitive level of recognition accuracy and real‐time performance. The results show that the model is well‐suited for deployment in embedded domains, including live entrance security checks, driver authorization, and in‐class attendance systems. The entire code of FN8 is available on GitHub.

Architectural Design Model Guided On-Demand Power Management of Energy-Efficient GPGPU for SLAM

Simultaneously localization and mapping (SLAM) is a core component in many embedded domains, e.g., robots, augmented and virtual reality. Due to SLAM’s high demand on computation resources, general-purpose graphic processing units (GPGPUs) are often used as its processing engine. Meanwhile, embedded systems usually have strict power constraint. Thus, how to deliver required performance for SLAM, yet still meet the power limit, is a great challenge faced by GPGPU designer. In this work, we discover the general principles of designing energy-efficient GPGPU for SLAM as “many SMs, enough SPs and registers, small caches”, by analyzing the implication of individual design parameters on both performance and power. Then, we conduct large-scale design space exploration and fit the Pareto frontier with a two-term exponential model. Further, we construct gradient boosting decision tree (GBDT)-based design models to predict the performance and power given the design parameters. The evaluation shows that our GBDT-based models can achieve [Formula: see text]3% mean average percentage error, which significantly outperform other machine learning models. With these models, a kernel’s requirement on hardware resources can be well understood. Based on such knowledge, we introduce design model guided power management strategies, including power gating and dynamic frequency and voltage scaling (DFVS). Overall, by combining these two power management strategies, we can improve the energy delay product by 36%.

Stability of inverse source problem for a transmission wave equation with multiple interfaces of discontinuity

In this paper, we consider a transmission wave equation in N embedded domains with multiple interfaces of discontinuous coefficients in ℝ2. We study the global stability in determining the source term from a one-measurement data of wavefield velocity in a subboundary over a time interval. We prove the stability estimate for this inverse source problem by a combination of the local hyperbolic/elliptic Carleman estimates and the Fourier-Bros-Iagolniter transformation. Our method could be generalized to general dimensions since the weight functions and Carleman estimates are independent of the dimensions.

An inverse problem for the transmission wave equation with Kelvin–Voigt damping

ABSTRACT In this paper, we consider a transmission wave problem with Kelvin–Voigt damping in two embedded domains in . We construct a global Carleman estimate for the transmission strongly damped wave equation with discontinuous coefficients. With the new Carleman estimate, we prove the Lipschitz stability and uniqueness of the inverse problem of determining the coefficient of the zeroth-order term in the equation with a single measurement observed in any small domain located in the outer domain.

An unfitted finite element method using level set functions for extrapolation into deformable diffuse interfaces

We explore a new way to handle flux boundary conditions imposed on level sets. The proposed approach is a diffuse interface version of the shifted boundary method (SBM) for continuous Galerkin discretizations of conservation laws in embedded domains. We impose the interface conditions weakly and approximate surface integrals by volume integrals. The discretized weak form of the governing equation has the structure of an immersed boundary finite element method. That is, integration is performed over a fixed fictitious domain. Source terms are included to account for interface conditions and extend the boundary data into the complement of the embedded domain. The calculation of these extra terms requires (i) construction of an approximate delta function and (ii) extrapolation of embedded boundary data into quadrature points. We accomplish these tasks using a level set function, which is given analytically or evolved numerically. A globally defined averaged gradient of this approximate signed distance function is used to construct a simple map to the closest point on the interface. The normal and tangential derivatives of the numerical solution at that point are calculated using the interface conditions and/or interpolation on uniform stencils. Similarly to SBM, extrapolation of data back to the quadrature points is performed using Taylor expansions. Computations that require extrapolation are restricted to a narrow band around the interface. Numerical results are presented for elliptic, parabolic, and hyperbolic test problems, which are specifically designed to assess the error caused by the numerical treatment of interface conditions on fixed and moving boundaries in 2D.

The elastic inclusion problem in the (amplitude) phase field crystal model

In many processes for crystalline materials such as precipitation, heteroepitaxy, alloying, and phase transformation, lattice expansion or compression of embedded domains occurs. This can significantly alter the mechanical response of the material. Typically, these phenomena are studied macroscopically, thus neglecting the underlying microscopic structure. Here we present the prototypical case of an elastic inclusion described by a mesoscale model, namely a coarse-grained phase-field crystal model. A spatially-dependent parameter is introduced into the free energy functional to control the local spacing of the lattice structure, effectively prescribing an eigenstrain. The stress field obtained for an elastic inclusion in a 2D triangular lattice is shown to match well with the analytic solution of the Eshelby inclusion problem.

Advancing DSP into HPC, AI, and beyond: challenges, mechanisms, and future directions

Digital Signal Processors (DSPs) have been widely used in embedded domains, delivering high performance with ultra-low power consumption. Such promises make it attractive for more domains that DSP was not an option before. To show how DSP lives up to these promises, we review two milestone DSPs: FT-Matrix and FT-Matrix2, which are designed by National University of Defense Technology with the purpose of advancing DSPs into the era of higher performance computing, AI, and even beyond. We demonstrate that the key challenges lie in the orchestration of huge computation resources and efficient data supply sub-system design. We show the key mechanisms in both FT-Matrix and FT-Matrix2 targeting these challenges, and also come up with possible future directions for enabling DSPs for a wider scope of applications.

Visually meaningful image encryption based on universal embedding model

Visually meaningful image encryption (VMIE) means that a plain image can be encrypted into a visually meaningful cipher image (VMCI), which makes the secret more imperceptible than noise-like cipher images. Here, we first present a universal embedding model (UEM) and further present a new UEM-based VMIE algorithm. The plain image is pre-encrypted and then embedded into the integer wavelet subbands of the host image in a dynamic way. In order to avoid the overflow, a threshold limiting function is used to modify the range of pixel values of the host image. To adapt different types of wavelet transform subbands, a UEM is proposed to be used to embed the secret information domain into the host domain. Moreover, in the embedding process, a four-dimensional discrete chaotic system is used to ensure the security of embedding. The numbers of embedded bits in the four embedded domains can be adjusted flexibly. A traversal algorithm is designed to find the optimal numbers of embedded bits for different types of wavelet transform in order to achieve an optimal visual quality of cipher images. A matrix-bit-depth-conversion algorithm is designed where a large matrix with low bit depth can be transformed into a small matrix with high bit depth to meet the input requirements of UEM, which means that the size of the plain image is not limited to a quarter of the size of the host image. Simulation results and performance comparisons show that the proposed VMIE algorithm can achieve a better visual quality than existing VMIE algorithms.

Spectral aspects of Nitsche’s method on nonconforming meshes

Nitsche’s method is an effective framework for the solution of problems involving embedded domains. Weak enforcement of Dirichlet boundary and interface conditions engenders additional active degrees of freedom compared to the corresponding kinematically admissible formulation, and hence additional solutions in eigenvalue problems. The original and added eigenpairs are designated proper and complementary, respectively. The number of complementary pairs equals the number of degrees of freedom that would be constrained in the kinematically admissible formulation. We investigate the number of complementary pairs that arise in representative nonconforming configurations of bilinear quadrilaterals. Algebraic elimination of the added degrees of freedom from the Nitsche formulation yields a formulation with several advantageous features. Practical procedures for solving eigenvalue problems based on reduced methods are proposed.

Validating the Persian Intuitive Eating Scale-2 Among Breast Cancer Survivors Who Are Overweight/Obese.

Women with breast cancer are at risk of being overweight/obese which may consequently increase mortality. Intuitive eating is an adaptive eating behavior which might be beneficial for weight outcomes. The present study validated the Persian Intuitive Eating Scale-2 (IES-2) among overweight/obese Iranian females with breast cancer. Women who were overweight/obese with breast cancer (n = 762; mean ± SD age = 55.1 ± 5.7 years) completed the following questionnaires: IES-2, General Self-Efficacy Scale (GSE-6), Hospital Anxiety and Depression Scale (HADS), Short Form-12 (SF-12), Weight Bias Internalization Scale (WBIS), Body Appreciation Scale-2 (BAS-2), and Eating Attitudes Test (EAT-26). Confirmatory factor analysis (CFA) and Rasch analysis were applied to examine the psychometric properties of the IES-2. Associations between IES-2 score and other scale scores were assessed. CFA and Rasch analysis suggested that the Persian IES-2 had robust psychometric properties and all IES-2 items were meaningful in their embedded domains. The four-factor structure of the Persian IES-2 was confirmed. Concurrent validity was supported by the positive correlations between the IES-2 score and scores on the GSE-6, SF-12 mental component, and BAS-2. Negative correlations were found between the IES-2 score and the HADS (anxiety and depression subscales), WBIS, and EAT-26. The present study demonstrated that the Persian IES-2 is a well-designed instrument and is applicable for women who are overweight/obese with breast cancer.

Quality of life with pregnancy outcomes: Further evaluating item properties for refined Taiwan's FertiQoL

We assessed the reliability and validity of Taiwan's version of FertiQoL, with a focus on the association between quality of life (QoL) and in-vitro-fertilization (IVF) pregnancy. 410 women undergoing IVF treatment were included. QoL measured by Taiwan's version of FertiQoL was assessed before embryo transfer. Item properties were examined using corrected item-total correlation, Rasch mean-square (MnSq), and internal consistency. Known-group validity was assessed using IVF pregnancy (i.e., chemical pregnancy, ongoing pregnancy, live birth) as the outcomes of interest. Five FertiQoL items, namely Q4, Q5, Q15, Q21, and T5, had low corrected item-total correlation (i.e., -0.146-0.290) in their embedded domains; three other items, namely Q11, Q14, and T2, did not have acceptable MnSq values in the Rasch analysis (i.e., infit MnSq: 1.31-2.28; outfit MnSq: 1.95-4.57). These items were removed and a refined Taiwan's FertiQoL was generated. The internal consistency for the refined Taiwan's FertiQoL was improved (α=0.928) with the capability of distinguishing women who had successful live birth from those who had failed live birth (i.e., 72.40±12.71vs. 69.21±13.26; p=0.019). The study results demonstrate that the refined Taiwan's FertiQoL is valid and reliable, suggesting that this FertiQoL should refined to be culturally and language appropriate for Taiwanese population.

How is agile development currently being used in regulated embedded domains?

AbstractBackgroundAgile development shows benefits for software‐developing companies, eg, shorter time to market or stronger customer connections. Nonetheless, agile methods and practices are most often adapted to a specific context. Especially in regulated domains such as automotive, avionics, or medical, domain‐specific constraints need to be considered, and hence, Agile is often used only partially or not at all.ObjectiveThe goal of this study was to identify the state of the practice in using agile development as part of the development process in regulated embedded domains.MethodWe conducted a study using a combination of a series of interviews and an online questionnaire as data collection methods.ResultsThe responses of 50 participants showed that Agile, mostly in the form of an adapted form of Scrum, has already arrived in those domains, but mainly in noncritical projects and/or early project phases. This means there is further improvement potential, which was also confirmed by the participants regarding future usage.ConclusionsThe results of our state‐of‐the‐practice study provide a good stage for future work, especially for new approaches bringing more “agility” into regulated embedded domains.

Amorphous silicate nanoparticles with controlled Fe-Mg pyroxene compositions

The production of amorphous pyroxene nanoparticles (~20nm) with controlled Fe-Mg content is described. Homogenous particle compositions closely matching required target stoichiometries are obtained by drying a precursor gel under high vacuum conditions. The silicate nature of the particles is characterised using TEM, synchrotron radiation and FTIR. No oxide phase separation occurs, even at high Fe concentration. Structural domains exist within the nanoparticles that are typically ten times smaller than the physical particle size consistent with either a core-shell, or, random network with multiple embedded domains, particle structure. Thermal annealing below the crystallisation temperature allows the ordered domain size to be further reduced by a factor of ~2.

An Efficient Evolutionary Task Scheduling/Binding Framework for Reconfigurable Systems

Several embedded application domains for reconfigurable systems tend to combine frequent changes with high performance demands of their workloads such as image processing, wearable computing, and network processors. Time multiplexing of reconfigurable hardware resources raises a number of new issues, ranging from run-time systems to complex programming models that usually form a reconfigurable operating system (ROS). In this paper, an efficient ROS framework that aids the designer from the early design stages all the way to the actual hardware implementation is proposed and implemented. An efficient reconfigurable platform is implemented along with novel placement/scheduling algorithms. The proposed algorithms tend to reuse hardware tasks to reduce reconfiguration overhead, migrate tasks between software and hardware to efficiently utilize resources, and reduce computation time. A supporting framework for efficient mapping of execution units to task graphs in a run-time reconfigurable system is also designed. The framework utilizes an Island Based Genetic Algorithm flow that optimizes several objectives including performance, area, and power consumption. The proposed Island Based GA framework achieves on average 55.2% improvement over a single-GA implementation and an 80.7% improvement over a baseline random allocation and binding approach.

Schedule refinement for homogeneous multi-core processors in the presence of manufacturing-caused heterogeneity

Multi-core homogeneous processors have been widely used to deal with computation-intensive embedded applications. However, with the continuous down scaling of CMOS technology, within-die variations in the manufacturing process lead to a significant spread in the operating speeds of cores within homogeneous multi-core processors. Task scheduling approaches, which do not consider such heterogeneity caused by within-die variations, can lead to an overly pessimistic result in terms of performance. To realize an optimal performance according to the actual maximum clock frequencies at which cores can run, we present a heterogeneity-aware schedule refining (HASR) scheme by fully exploiting the heterogeneities of homogeneous multi-core processors in embedded domains. We analyze and show how the actual maximum frequencies of cores are used to guide the scheduling. In the scheme, representative chip operating points are selected and the corresponding optimal schedules are generated as candidate schedules. During the booting of each chip, according to the actual maximum clock frequencies of cores, one of the candidate schedules is bound to the chip to maximize the performance. A set of applications are designed to evaluate the proposed scheme. Experimental results show that the proposed scheme can improve the performance by an average value of 22.2%, compared with the baseline schedule based on the worst case timing analysis. Compared with the conventional task scheduling approach based on the actual maximum clock frequencies, the proposed scheme also improves the performance by up to 12%.

3D CV Descriptor on Parallel Heterogeneous Platforms

Embedded three-dimensional (3D) Computer Vision (CV) is considered a technology enabler for future consumer applications, attracting a wide interest in academia and industry. However, 3D CV processing is a computation-intensive task. Its high computational cost is directly related to the processing of 3D point clouds, with the 3D descriptor computation representing one of the main bottlenecks. Understanding the main computational challenges of 3D CV applications, as well as the key characteristics, enabling features, and limitations of current computing platforms, is clearly strategic to identify the directions of evolution for future embedded processing systems targeting 3D CV. In this work, an innovative and complex 3D descriptor (called SHOT) has been ported on a high-end and an embedded computing platform. The high-end system is composed by a high-performance Intel CPU coupled with a Nvidia GPU. The embedded platform is, instead, composed by an ARM-based processor, coupled with the STHORM accelerator. STHORM is a many-core low-power accelerator developed by ST Microelectronics, featuring up to 64 computational units. The SHOT descriptor has been parallelized using the OpenCL programming model for both platforms. Finally, we have performed an in-depth performance comparison and analysis between general-purpose processors and accelerators in both high-end and embedded domains, discussing and highlighting the main differences in the Hardware/Software (HW/SW) design methodologies and approaches between high-end and embedded systems targeting 3D CV applications.

An Efficient Framework for Floor-plan Prediction of Dynamic Runtime Reconfigurable Systems

<p>Several embedded application domains for reconfigurable systems tend to combine <br />frequent changes with high performance demands of their workloads such as image processing, wearable computing and<br />network processors. Time multiplexing of reconfigurable hardware resources raises a number of new issues, ranging <br />from run-time systems to complex programming models that usually form a Reconfigurable<br />hardware Operating System (ROS). The Operating System performs online task scheduling and handles resource management.<br />There are many challenges in adaptive computing and dynamic reconfigurable systems. One of the major understudied challenges<br />is estimating the required resources in terms of soft cores, Programmable Reconfigurable Regions (PRRs), <br />the appropriate communication infrastructure, and to predict a near optimal layout and floor-plan of the reconfigurable logic fabric. <br />Some of these issues are specific to the application being designed, while others are more general and relate to the underlying run-time environment.<br />Static resource allocation for Run-Time Reconfiguration (RTR) often leads to inferior and unacceptable results. <br />In this paper, we present a novel adaptive and dynamic methodology, based on a Machine Learning approach, for predicting and<br />estimating the necessary resources for an application based on past historical information.<br />An important feature of the proposed methodology is that the system is able to learn and generalize and, therefore, is expected to improve <br />its accuracy over time. The goal of the entire process is to extract useful hidden knowledge from the data. This knowledge is the prediction <br />and estimation of the necessary resources for an unknown or not previously seen application.<br /><br /></p>

Complex Tenses, Agreement and Wh-extraction

0. Introduction In this paper we provide an analysis of the syntax of tense in Berber and investigate the interaction between complex tenses and the Anti-Agreement Effect (AAE), which was first discussed by Ouhalla (1993). Our analysis attempts to unify the tense system of Berber and make an accurate distinction between tense and aspect in this language. In our analysis of complex tenses we propose that complex tense clauses are bi-clausal, i.e. their structure consists of two Tense projections, and show how that is compatible with the defectiveness of T in embedded domains. Our analysis provides empirical evidence for cyclic valuation/checking of Case (Chomsky 2000, 2001). We also present certain similarities between AAE in Berber and auxiliary raising/T-to-C in English, regarding cases of local wh-movement of subjects vs. objects. This paper is organized as follows: section 1 provides some background and offers an analysis of the tense system in Berber, section 2 analyzes complex tenses in this language, section 3 compares complex tense constructions to Exceptional Case Marking (ECM) constructions, section 4 discusses subject extraction and offers an analysis of AAE, and section 5 highlights the asymmetry between AAE in Berber and Tto-C raising in English.

Phonon dynamics and anharmonicity in phase segregated structural domains of MgZnO film

Phonon decay channels and anharmonicities in embedded domains in MgZnO film were studied via selective resonant Raman scattering at the elevated temperature regime up to 870 K. The resonant conditions provided by excitation with different ultraviolet laser lines enabled the detection of longitudinal optical (LO) phonons from domains with the wurtzite structure, and domains with the cubic rocksalt structure which lack inversion symmetry due to alloying. The phonon behavior was modeled in terms of three- and four-phonon decay processes using Ridley and Klemens type decay processes. It is found that the wurtzite phase displays dominantly three-phonon decay with a small four-phonon component. In contrast, the cubic phase displays a higher degree of anharmonicity in which the four-phonon processes contribute significantly to the temperature dependent frequency shift. At the elevated temperature range, the LO frequency shift rate is ∼−2.6 × 10−2 cm−1/K for the wurtzite structure while that of the cubic exhibits a much larger shift rate of ∼−1.6 × 10−1 cm−1/K. The larger anharmonicity of the domains with the cubic structure is discussed in terms of strain and deformation effects.