Portability Problems Research Articles

A dual fusion recognition model for sleep posture based on air mattress pressure detection

In order to solve the difficult portability problem of traditional non-invasive sleeping posture recognition algorithms arising from the production cost and computational cost, this paper proposes a sleeping posture recognition model focusing on human body structural feature extraction and integration of feature space and algorithms based on a specific air-spring mattress structure, called SPR-DE (SPR-DE is the Sleep Posture Recognition-Data Ensemble acronym form). The model combines SMR (SMR stands for Principle of Spearman Maximal Relevance) with horizontal and vertical division based on the barometric pressure signals in the human body’s backbone region to reconstruct the raw pressure data into strongly correlated non-image features of the sleep postures in different parts and directions and construct the feature set. Finally, the recognit-ion of the two sleep postures is accomplished using the AdaBoost-SVM integrated classifier. SPR-DE is compared with the base and integrated classifiers to verify its performance. The experimental results show that the amount of significant features helps the algorithm to classify different sleeping patterns more accurately, and the f1 score of the SPR-DE model determined by the comparison experiments is 0.998, and the accuracy can reach 99.9%. Compared with other models, the accuracy is improved by 2.9% ~ 7.7%, and the f1-score is improved by 0.029 ~ 0.076. Therefore, it is concluded that the SMR feature extraction strategy in the SPR-DE model and the AdaBoost-SVM can achieve high accuracy and strong robustness in the task of sleep posture recognition in a small area, low-density air-pressure mattress, taking into account the comfort of the mattress structural design and the sleep posture recognition, integrated with the mattress adaptive adjustment system.

Design and realization of high-resolution optoelectronic imaging system

Abstract Aiming at the demand for a large field of view, extreme temperature difference, and high resolution in various fields, as well as the problems of poor real-time and low portability of traditional photoelectric imaging systems. A distributed photoelectric imaging system based on FPGA is designed and implemented in this paper. The entire system comprises an optical system, a photoelectric imaging system, and a computer communication system. The optical imaging lens incorporates an atomic filter for filtering, and the imaging detector enables real-time, high signal-to-noise ratio, high resolution, and large field-of-view imaging in the upper computer. The image processing module of the system utilizes the feature information of the image in the local area to calculate the direction of each point, ensuring that the feature description vector has the stable property of rotational invariance in the direction. In terms of design parameters, the underflight imaging optical system has a focal length of 46.00 m, a near-infrared spectral channel with a bandpass of 1.2 ~ 1.375 μm, a resolution of 1080 × 2040 high pixels, an F-number of 4, an imaging CCD with a pixel size of 18 μm and an imaging quality that reaches the diffraction limit, and the optical system of each channel has a compact structure. The analysis results show that in this set of high-resolution optoelectronic imaging systems, under different working conditions, the root-mean-square wavefront error of the primary mirror is less than the standard value of 50 nm, and the peak difference is less than the standard value of 200 nm, which meets the high standard requirements of optical imaging.

Методика организации процесса мониторинга распределенных информационных систем

This article is devoted to the methodology of organizing the process of monitoring of distributed information systems. The article considers the general concept of building the process of information security monitoring. Special attention is paid to such disadvantages of distributed systems as problems of system administration, problems of limited scalability of distributed systems and problems of software portability. It was concluded that at present there is no unified approach to eliminate these disadvantages when building a monitoring process. The model of decentralized distributed system for which the methodology of monitoring process organization is developed is given. Three approaches to the organization of monitoring process of distributed information systems are described, namely the organization of monitoring of network activity of information system, the organization of monitoring of host activity of information system and mixed approach. The mixed approach based on monitoring of network and host activity is used in the methodology. The process of prioritization of sources of information security events is considered, which includes the assessment of IS risks, identification of actual IS threats and identification of critical assets of the organization. As a result, a methodology for organizing the process of monitoring distributed information systems is proposed, which consists of four stages: risk calculation, identification of actual threats, prioritization of information security event sources and connection of selected sources to the information security event monitoring system.

The Scheme of Movable DC Ice Melting Device Based on the Engine-Generator Topology

In this article, an entire scheme of DC ice-melting devices based on the engine-generator topology is proposed to solve the problem of poor portability caused by the current devices. It is found that the engine-generator topology suffers from a power mismatch when starting with load, which may eventually lead to starting failure. A soft-start strategy is proposed to control the power required by the load by controlling the duty cycle of the switching tube to achieve real-time power matching. Compared with the most popular phase-controlled rectifier DC ice melting device, the entire scheme of the device is proposed, which not only achieves continuous voltage and current adjustment but also effectively reduces the ripple of the output and control complexity. The feasibility of the proposed soft-start strategy and the entire scheme of the device is verified by simulation results.

Toward Unified Adaptive Teleoperation Based on Damping ZNN for Robot Manipulators With Unknown Kinematics

Traditional teleoperation systems are usually designed for a single class of slave robots and require the specific kinematic model. This leads to the problems of high computational cost, poor robustness, and poor portability in traditional teleoperation systems. In this paper, a unified adaptive teleoperation system is proposed for different kinds of slave robots. To this end, a closed-loop control system based on damping zeroing neural network (DampZNN) is proposed to achieve the unified kinematic control of both the redundant robot and the continuum robot with unknown kinematics. The control system is constructed based on two DampZNNs, which are utilized to estimate the unknown kinematic model and to solve the inverse kinematics problem respectively. By combining the DampZNN control system with teleoperation technology, a unified adaptive teleoperation system is proposed for human operators to teleoperate both the redundant slave robot and the continuum slave robot easily. The efficacy of the proposed teleoperation system is verified by experiments based on different slave robots and the advantages of the proposed teleoperation system are revealed by comparative studies.

Underwater Acoustically Guided Docking Method Based on Multi-Stage Planning

Autonomous underwater vehicles (AUVs) are important in areas such as underwater scientific research and underwater resource collection. However, AUVs suffer from data portability and energy portability problems due to their physical size limitation. In this work, an acoustic guidance method for underwater docking is proposed to solve the problem of persistent underwater operation. A funnel docking station and an autonomous remotely operated vehicle (ARV) are used as the platform for designing the guidance algorithms. First, the underwater docking guidance is divided into three stages: a long-range approach stage, a mid-range adjustment stage and a short-range docking stage. Second, the relevant guidance strategy is designed for each stage to improve the docking performance. Third, a correction method based on an ultra-short baseline (USBL) system is proposed for the ARV’s estimate of the depth, relative position and orientation angle of the docking station. To verify the feasibility of the docking guidance method, in this work, tests were performed on a lake and in a shallow sea. The success rate of autonomous navigation docking on the lake was 4 out of 7. The success rate of acoustic guidance docking on the lake and in the shallow sea were 11 out of 14 and 6 out of 8, respectively. The experimental results show the effectiveness of the docking guidance method in lakes and shallow seas.

Ultra-high baud rate VLF magnetoelectric antenna based on Rosen-type composite

Long-wave antennas are extensively used in special environment communications, such as underwater and underground applications, but the huge size of traditional electrical antennas restricts their applications. The emergent acoustically excited magnetoelectric (ME) antennas is expected to solve the portability problem. However, the contradiction between the radiation intensity and modulation rate (i.e., baud rate) of ME antenna remains an obstacle to its development. Here, we propose a very low frequency (VLF, 3–30 kHz) ME antenna based on a Rosen-type magnetostrictive-piezoelectric ME composite, which collaboratively optimizes both radiation intensity and transmission rate. The radiation intensity and efficiency of the proposed ME antenna were, respectively, two and three orders of magnitude higher than those of a same-sized loop antenna. A VLF communication system based on the Rosen-type ME antenna utilized amplitude shift keying (ASK) modulation was demonstrated. The system achieved an ultra-high baud rate of up to 2 kbaud (i.e., 2 kbps bit rate), confirming the feasibility of this approach.

Progressive Learning of a Multimodal Classifier Accounting for Different Modality Combinations.

In classification tasks, such as face recognition and emotion recognition, multimodal information is used for accurate classification. Once a multimodal classification model is trained with a set of modalities, it estimates the class label by using the entire modality set. A trained classifier is typically not formulated to perform classification for various subsets of modalities. Thus, the model would be useful and portable if it could be used for any subset of modalities. We refer to this problem as the multimodal portability problem. Moreover, in the multimodal model, classification accuracy is reduced when one or more modalities are missing. We term this problem the missing modality problem. This article proposes a novel deep learning model, termed KModNet, and a novel learning strategy, termed progressive learning, to simultaneously address missing modality and multimodal portability problems. KModNet, formulated with the transformer, contains multiple branches corresponding to different k-combinations of the modality set S. KModNet is trained using a multi-step progressive learning framework, where the k-th step uses a k-modal model to train different branches up to the k-th combination branch. To address the missing modality problem, the training multimodal data is randomly ablated. The proposed learning framework is formulated and validated using two multimodal classification problems: audio-video-thermal person classification and audio-video emotion classification. The two classification problems are validated using the Speaking Faces, RAVDESS, and SAVEE datasets. The results demonstrate that the progressive learning framework enhances the robustness of multimodal classification, even under the conditions of missing modalities, while being portable to different modality subsets.

The Navigation System of a Logistics Inspection Robot Based on Multi-Sensor Fusion in a Complex Storage Environment.

To reliably realize the functions of autonomous navigation and cruise of logistics robots in a complex logistics storage environment, this paper proposes a new robot navigation system based on vision and multiline lidar information fusion, which can not only ensure rich information and accurate map edges, but also meet the real-time and accurate positioning and navigation in complex logistics storage scenarios. Simulation and practical verification showed that the robot navigation system is feasible and robust, and overcomes the problems of low precision, poor robustness, weak portability, and difficult expansion of the mobile robot system in a complex environment. It provides a new idea for inspection in an actual logistics storage scenario and has a good prospective application.

Social Work Licensure Portability: A Necessity in a Post-COVID-19 World.

COVID-19 highlights the need for portability of social work licensure to be a priority. The Association of Social Work Boards (ASWB) spearheaded some initiatives, such as the creation and promotion of the Social Work Registry and Model Social Work Practice Act, with the hope that these efforts would enhance the ability of social workers to be licensed in multiple states. Neither has solved the portability problem. Licensure endorsement, an approach historically supported by ASWB, does not have the advantages of mutual recognition that is being supported by other professions to facilitate interstate practice. This article, the first written on licensure portability in the social work scholarly literature, examines existing licensure portability models and supports the establishment of a social work interstate compact to overcome barriers to social work mobility and access to client care.

Multisensory Flexible Braille Interactive Device Based on Liquid Crystal Elastomers

Traditional electronic braille devices’ rigid and complex structure limits their portability while satisfying braille output. Main-chain monodomain liquid crystal elastomers (m-LCEs) can achieve high contraction deformation under external stimulation conditions; it has broad application prospects in the human–machine interaction with the biological tissue safety and flexibility of LCEs. A multisensory flexible braille interactive device based on LCEs is proposed in this article. It utilizes the good reversible shape-memory performance of m-LCEs to solve the problems of complex structure design, poor portability, high cost, and low control stability in traditional rigid mechanical braille readers. The fixed-point stretchable convex lattice and the nonactuation performance-based film are accurately distinguished and fabricated by compression molding. Combined with the ultrathin flexible electric heating layer, the reversible contraction of the braille point is realized, and the braille point is given the dual perception of height difference and temperature difference. Moreover, matching circuit design can realize braille input by press and braille output by convex–concave conversion. Furthermore, we try to introduce thermochromic powders, referring to the principle of light-emitting diode (LED) imaging, to transform the pattern concept of visually impaired people in minds into color information that ordinary people can observe.

Temporal Variation and Component Allocation Characteristics of Geometric and Physical Parameters of Maize Canopy for the Entire Growing Season

The accurate monitoring of crop parameters is important for crop yield prediction and canopy parameter inversion from remote sensing. Process-based and semi-empirical crop models are the main approaches to modeling the temporal changes in crop parameters. However, the former requires too many input parameters and the latter has the problem of poor portability. In this study, new semi-empirical geometric and physical parameters of the maize canopy model (GPMCM) crop model adapted to northeast China were proposed based on a time-series field datasets collected from 11 sites in the Nong’an and Changling Counties of Jilin Province, China, during DOY (day of year) 163 to DOY 278 in 2021. The allocation characteristics of and correlations between each maize canopy parameter were investigated for the whole growing season using the 22 algorithms of crop parameters, and the following conclusions were obtained. (1) The high correlation coefficient (R mean = 0.79) of LAI with other canopy parameters indicated that it was a good indicator for predicting other parameters. (2) Better performance was achieved by the regression method based on the two-stage simulation. The root-mean-squared error (RMSE) of geometric parameters including maize height, stem long radius, and short radius were 12.91 cm, 0.74 mm, and 0.73 mm, respectively, and the RMSE of the physical parameters including the FAGB, AGB, VWC, and RWC of the stems and leaves, ranged from 0.05 kg/m2 to 4.24 kg/m2 (2.0% to 12.9% for mean absolute percentage error (MAPE)). (3) The extension of the field-scale GPMCM to the 500 m MODIS-scale still provided a good accuracy (MAPE: 11% to 18.5%) and confirmed the feasibility of the large-scale application of the GPMCM. The proposed CPMCM can predict the temporal dynamics of maize geometric and physical parameters, and it is helpful to establish the forward and reverse models of remote sensing and improve the inversion accuracy of crop parameters.

Parallelism Reduction Methods in the High-Level VLSI Synthesis Implementation

The problems and solutions in the field of ensuring architectural independence and implementation of digital integrated circuits end-to-end design processes are considered. The paper focuses on the need to find a solution to the problem of program portability during the development of integrated circuits. A review of the main software and tools used to design digital circuits (Verilog, System-C, Handel-C, Lava, Hydra, Wired, COLAMO, Chisel and etc.) is presented. The method and language of parallel programming for functional flow synthesis of design solutions PIFAGOR is presented. The example of the source and generated code in the PIFAGOR and Verilog languages is given. During the method implementation, the tasks of reducing parallelism and estimating the occupied resources were highlighted. The main feature of the developed method is the introduction of the additional layer (HDL graph) into the synthesis process. Algorithms for the parallelism reduction have been developed. This method is demonstrated on the example of parallelism reduction while going to the FPGA platform solving the problem of calculating a 4-point FFT (Fast Fourier Transform). As part of the solution of this task, an assessment of memory resources and an assessment of computing resources were carried out. The results of software tools development for design support including the parallelism reduction preprocessor and resource estimation preprocessor and practical VLSI projects are presented.

Applying Intel's oneAPI to a machine learning case study

AbstractDifferent technologies and approaches exist to work around the performance portability problem. Companies and academia work together to find a way to preserve performance across heterogeneous hardware using a unified language, one language to rule them all. Intel's oneAPI appears with this idea in mind. In this article, we try the new Intel solution to approach heterogeneous programming, choosing machine learning as our case study. More precisely, we choose Caffe, a machine learning framework that was created six years ago. Nevertheless, how would it be to make Caffe again from the beginning, using a fresh new technology like oneAPI? In terms of not only the ease of programming‐because only one source code would be needed to deploy Caffe to CPUs, GPUs, FPGAs, and accelerators (platforms that oneAPI currently supports)‐but also performance, where oneAPI may be capable of taking advantage of specific hardware automatically. Is Intel's oneAPI ready to take the leap?

The 60th Anniversary of TFTs and the Evolution of High‐Resolution Displays

The 60th Anniversary of TFTs and the Evolution of High‐Resolution Displays

Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort

The low portability of polygenic scores (PGSs) across global populations is a major concern that must be addressed before PGSs can be used for everyone in the clinic. Indeed, prediction accuracy has been shown to decay as a function of the genetic distance between the training and test cohorts. However, such cohorts differ not only in their genetic distance but also in their geographical distance and their data collection and assaying, conflating multiple factors. In this study, we examine the extent to which PGSs are transferable between ancestries by deriving polygenic scores for 245 curated traits from the UK Biobank data and applying them in nine ancestry groups from the same cohort. By restricting both training and testing to the UK Biobank data, we reduce the risk of environmental and genotyping confounding from using different cohorts. We define the nine ancestry groups at a sub-continental level, based on a simple, robust, and effective method that we introduce here. We then apply two different predictive methods to derive polygenic scores for all 245 phenotypes and show a systematic and dramatic reduction in portability of PGSs trained using Northwestern European individuals and applied to nine ancestry groups. These analyses demonstrate that prediction already drops off within European ancestries and reduces globally in proportion to genetic distance. Altogether, our study provides unique and robust insights into the PGS portability problem.

Half a century later and we're back where we started: How the problem of locality turned in to the problem of portability

In the 1970s, Lewontin sparked a debate about a problem of locality, by making the case that any given heritability estimate is local to the original population and environment studied, and could not be generalized to other populations and environments. Nearly 50 years later, a new problem of portability has emerged: the predictive accuracy of polygenic scores diminishes when applied to populations whose characteristics are different from the original population sample. This paper briefly reviews the nature of each problem and analyzes their similarities and differences in three areas: 1) conceptual underpinnings, 2) causal explanations, and 3) practical, social, and political implications. Although conceptually and methodologically different from the problem of locality in important respects, the problem of portability facing contemporary genomics today should come as no surprise, as it is an inevitable outcome of the kinds of problematic inferences detailed by Lewontin nearly half a century ago.

Reformulation of the performance portability metric

SummaryThe 3‐P challenge of high‐performance programming—performance, portability and productivity—has become more difficult than ever in the age of heterogeneous computing. It would be naïve to think that the performance portability problem can be completely solved, but it can certainly be reduced and made tolerable. However, first and foremost, an agreement is needed on what it means for an application to be performance portable. Unfortunately, there is still no consensus in the scientific community on a workable definition of the term performance portability. Several years ago, a comprehensive effort was made to formulate a novel definition of performance portability and an associated metric. Since the new metric was first introduced, it has been widely adopted by the scientific community, and many advanced studies have used it. Unfortunately, the definition of the new metric has flaws. This article presents a proof of the theoretical flaws in the definition of the new metric, considers the practical implications of these flaws as reflected in many studies that have used it in recent years, and proposes a revised metric that addresses the flaws and provides guidelines on how to use it correctly.

A Pneumatic Generator Based on Gas-Liquid Reversible Transition for Soft Robots

The soft robots actuated by pressure, cables, thermal, electrosorption, combustion and smart materials are usually faced with the problems of poor portability, noise, weak load capacity, small deformation and high driving voltages. In this paper, a novel pneumatic generator for soft robots based on the gas-liquid reversible transition is proposed, which has the advantages of large output force, easy deformation, strong load capacity and high flexibility. The pressure of the pneumatic generator surges or drops flexibly through the reversible transformation between liquid and gas phase, making the soft actuator stretch or contract regularly, without external motors, compressors and pressure-regulating components. The gas-liquid reversible-transition actuation process is modeled to analyze its working mechanism and characteristics. The pressure during the pressurization stage increases linearly with a rate regulated by the heating power and gas volume. It decreases exponentially with the exponential term as a quadratic function of time at the fast depressurization stage, while with the exponential term as a linear function of time at the slow depressurization stage. The drop rate can be adjusted by changing the gas volume and cooling conditions. Furthermore, effectiveness has been verified through experiments of the prototype. The pressure reaches 25 bar with a rising rate of +3.935 bar/s when 5 mL weak electrolyte solution is heated at 800 W, and the maximum depressurization rate in air cooling is –3.796 bar/s. The soft finger actuated by the pneumatic generator can bend with an angular displacement of 67.5°. The proposed pneumatic generator shows great potential to be used for the structure, driving and sensing integration of artificial muscles.

Оптимизация графов потока управления в промежуточных представлениях языка функционально-потокового параллельного программирования

Functional dataflow programming languages are intended for the development of architecture-independent parallel programs and support the control of computations based on data availability. Due to the fact that at present parallel computing systems are very widespread, and their programming in imperative languages is associated with portability problems, the development of architecturally independent parallel programming tools is an urgent task. When such a program is translated, intermediate representations are formed as the information graph and the corresponding control graph. During program execution, data readiness signals are transmitted along the arcs of the control graph. An explicit selection of the control graph allows us not only to change the computational control strategies and ensure the adaptation of the program to the architecture features, but also to apply specific methods for optimizing control dependencies. The paper proposes transformation methods that provide optimization of the control graph. When generating a control graph from an informational one, redundant arcs are introduced into it, the removal of which does not affect the result of the program, but leads to its more efficient execution. It is shown that in dataflow programs, in addition to control dependencies inherent in other programming languages, additional ones associated with the implementation features of deferred or conditional computations described by delayed lists arise. A formal description of redundant dependencies of various types is given, as well as an effective algorithm for their identification. The developed approach can be applied to such dataflow programming languages as PIFAGOR and Smile.