Basic Configurations Research Articles

Optimization of steady spin prediction by nonlinear iterative inversion algorithm

PurposeSince the inception of aircraft, the phenomenon of spin has persistently accompanied aircraft, and research into spin has been ongoing. This paper aims to introduce an optimization technique to enhance the traditional geometric method for predicting steady spin, aiming to achieve more precise predictive outcomes.Design/methodology/approachTo begin with, the force and moment equations used for motion analysis are initially presented, followed by the establishment of the motion model. Subsequently, the forward problem is set up, and the equilibrium solutions for the left and right spins of the aircraft are determined using the geometric method under the basic and wingtip configurations, thus solving the forward problem. In the final stage, nonlinear inversion is applied, and the inversion objective function is formulated based on the least squares approach. Through iterative processes, the measured data are interpolated, leading to the acquisition of the accurate equilibrium solution.FindingsThe findings indicate that the utilization of the nonlinear iterative inversion algorithm has effectively optimized the geometric method, yielding favorable outcomes. Postoptimization, the prediction accuracy has been enhanced, and the error has significantly diminished when compared to the preoptimization results.Originality/valueThe nonlinear inversion algorithm is used to refine the steady spin prediction for general aviation aircraft. This approach significantly mitigates the precision issues inherent in the forward problem. As demonstrated through the simulations provided, the application of the nonlinear iterative algorithm to resolve the inversion function yields promising optimization outcomes.

Numerical analysis of the effects of pores on propagating guided waves

The present numerical study aims to analyze the effect of pores on propagating guided waves while outlining the relevance of pore formation and its significance to structural properties. The primary focus of this study was on the pores present in planar carbon fiber-reinforced polymer (CFRP) parts. The wavefield data were generated by applying the elastodynamic finite integration technique (EFIT) solver AE3D, allowing for a systematic analysis based on fully controllable configurations and noise-free data. An isotropic material model was used to simplify the modeling of the anisotropic CFRP by assuming the averaged quasi-isotropic properties of the CFRP in all directions. More than 220 specimens containing single pores or four basic configurations of pore accumulations were modeled and analyzed in terms of their effect on the out-of-plane component of the propagating guided waves. Analysis of the guided wavefield data focused on the direction-dependent maximum amplitude differences and deviations in the wavefield energy. Mode- and wavenumber-specific amplitude loss along the centerline was analyzed using a matrix pencil algorithm. Finally, principal component analysis (PCA) was conducted to examine deviations caused by the presence of pores. Analysis of the wavefield effects of the pores for each specific configuration showed good differentiation between the considered pore volume groups. At the same time, the effects of the pores were shown to be significantly dependent on the pore configuration in terms of orientation and morphological properties. Associated with this, the intersecting outcome ranges for different pore volume groups were evident when all the pore configurations were considered simultaneously.

Single channel sound source localization by using combinations of multiple tubes

A method for localizing the direction arrival of the sound source with a single channel is proposed with the configuration of system consists of a single channel acoustic sensor and multiple inlets with specific path length of tubes or pipes. The time delay of arrival at each inlet can be estimated from the autocorrelation function measured at the sensor and the positions of peak in autocorrelation function are changed according to the incidence angle. By using this concept, the basic configurations are considered and the related investigations are conducted as solutions to several problems that need to be solved. The proposed concept is validated experimentally in anechoic chamber and outdoor conditions. As a method to expand the range of observation angle, the configuration with difference length is investigated and it is confirmed that the unique solution for the whole direction can be obtained by a combination of tubes and inlets.

The Information Length Concept Applied to Plasma Turbulence.

A methodology to study statistical properties of anomalous transport in fusion plasma is investigated. Three time traces generated by the full-f gyrokinetic code GKNET are analyzed for this purpose. The time traces consist of heat flux as a function of the radial position, which is studied in a novel manner using statistical methods. The simulation data exhibit transport processes with both medium and long correlation length along the radius. A typical example of a phenomenon with long correlation length is avalanches. In order to investigate the evolution of the turbulent state, two basic configurations are studied, one flux-driven and one gradient-driven with decaying turbulence. The information length concept in tandem with Boltzmann-Gibbs and Tsallis entropy is used in the investigation. It is found that the dynamical states in both flux-driven and gradient-driven cases are surprisingly similar, but the Tsallis entropy reveals differences between them. This indicates that the types of probability distribution function are nevertheless quite different since the higher moments are significantly different.

Optimizing feature fusion for improved zero-shot adaptation in text-to-speech synthesis

In the era of advanced text-to-speech (TTS) systems capable of generating high-fidelity, human-like speech by referring a reference speech, voice cloning (VC), or zero-shot TTS (ZS-TTS), stands out as an important subtask. A primary challenge in VC is maintaining speech quality and speaker similarity with limited reference data for a specific speaker. However, existing VC systems often rely on naive combinations of embedded speaker vectors for speaker control, which compromises the capture of speaking style, voice print, and semantic accuracy. To overcome this, we introduce the Two-branch Speaker Control Module (TSCM), a novel and highly adaptable voice cloning module designed to precisely processing speaker or style control for a target speaker. Our method uses an advanced fusion of local-level features from a Gated Convolutional Network (GCN) and utterance-level features from a gated recurrent unit (GRU) to enhance speaker control. We demonstrate the effectiveness of TSCM by integrating it into advanced TTS systems like FastSpeech 2 and VITS architectures, significantly optimizing their performance. Experimental results show that TSCM enables accurate voice cloning for a target speaker with minimal data through both zero-shot or few-shot fine-tuning of pretrained TTS models. Furthermore, our TSCM-based VITS (TSCM-VITS) showcases superior performance in zero-shot scenarios compared to existing state-of-the-art VC systems, even with basic dataset configurations. Our method’s superiority is validated through comprehensive subjective and objective evaluations. A demonstration of our system is available at https://great-research.github.io/tsct-tts-demo/, providing practical insights into its application and effectiveness.

Recent Advances in Electrochemical Cell Design for Concurrent Chemical Production and Electricity Generation

AbstractElectricity generation and chemical production are both critical cornerstone for modern society. Integrating electricity output and high value chemical production in an electrochemical system is highly attractive both environmentally and sustainably. In this review, we summarize the recent advances in the development of these multifunctional devices (electrocatalytic flow batteries) that could generate both electricity and high value chemicals through rational coupling of half‐electrode reactions, covering the basic principles, device configurations, and applications. We also discuss the current challenges and suggest potential research directions.

An Investigation on Hardware-Aware Vision Transformer Scaling

Vision Transformer (ViT) has demonstrated promising performance in various computer vision tasks, and recently attracted a lot of research attention. Many recent works have focused on proposing new architectures to improve ViT and deploying it into real-world applications. However, little effort has been made to analyze and understand ViT’s architecture design space and its implication for hardware costs on different devices. In this work, by simply scaling ViT’s depth, width, input size, and other basic configurations, we show that a scaled vanilla ViT model without bells and whistles can achieve comparable or superior accuracy-efficiency trade-off than most of the latest ViT variants. Specifically, compared with DeiT-Tiny, our scaled model achieves a ↑ 1.9% higher ImageNet top-1 accuracy under the same FLOPs and a ↑ 3.7% better ImageNet top-1 accuracy under the same latency on an NVIDIA Edge GPU TX2. Motivated by this, we further investigate the extracted scaling strategies from the following two aspects: (1) can these scaling strategies be transferred across different real hardware devices ? and (2) can these scaling strategies be transferred to different ViT variants and tasks ?. For (1), our exploration, based on various devices with different resource budgets, indicates that the transferability effectiveness depends on the underlying device together with its corresponding deployment tool. For (2), we validate the effective transferability of the aforementioned scaling strategies obtained from a vanilla ViT model on top of an image classification task to the PiT model, a strong ViT variant targeting efficiency as well as object detection and video classification tasks. In particular, when transferred to PiT, our scaling strategies lead to a boosted ImageNet top-1 accuracy of from 74.6% to 76.7% (↑ 2.1%) under the same 0.7G FLOPs. When transferred to the COCO object detection task, the average precision is boosted by ↑ 0.7% under a similar throughput on a V100 GPU.

Quantitative characterization of thin-interbedded coal measure reservoir configurations in the Wujiu depression, inner Mongolia: Sedimentary controlling mechanisms

Thin-interbedded coal measure reservoirs are important unconventional gas reservoirs. The lithology of these reservoirs is complicated, with rapid vertical changes, making accurate description difficult. Based on the thin-interbedded coal-bearing strata in the Wujiu Depression in eastern Inner Mongolia, China, this study constructs changes in lithofacies based on a Markov mathematical and statistical model. The Shengli subdepression mainly features a lithofacies sequence of uniform coal-mud-sand cycles and other small-scale symmetrical sedimentary cycles. In the Moguai–Shiwalu subdepression, lake hydrodynamics primarily affect coal–mudstone and mudstone–sandstone double-cycle lithofacies sequences and small-scale asymmetric sedimentary cycles. The Markov model and the Ward minimum variance method were used to quantitatively couple a reservoir lithologic sequence and bed thickness configuration, and five basic configurations of the composite reservoir of the Damoguaihe Formation in the study area were obtained: (1) multiseam interbedded configuration, (2) multiseam interbedded configuration with an intermediate number of seams, (3) interbedded configuration with an intermediate number or few seams (with thick mudstone or sandstone layers), (4) interbedded configuration with few seams (large spacings between adjacent coal seams) and (5) thickly interbedded configuration. The sedimentary facies mechanism controlling the spatial distribution pattern of composite reservoirs is discussed. It is concluded that the sedimentary system domain and lake size have a significant effect on the configuration of composite reservoirs. For small terrestrial lakes, the stability of sedimentary environment and the rapid and frequent rise and fall of the lake surface results in significant differences in coal accumulation in a short distance from the edge to the center.

The Anatomical Variation of the Distal Anterior Cerebral Artery: An Angiographic Study in a Greek Population Sample.

Objective The current retrospective angiographic study establishes the rates of variants in the distal anterior cerebral artery (DACA) in a sample of the Greek population. Methods Data were collected from 456 patients who underwent two-dimensional (2D) or three-dimensional (3D) digital subtraction angiography (DSA) of the carotid and vertebral arteriesbilaterally. The study focused on patients with good visualization of the anterior and posterior circulations and employed magnetic resonance (MR) or computed tomography (CT) angiography for 3D reconstruction. The anterior cerebral artery (ACA) was classified into one of its two basic configurations, that is, with or without the callosomarginal artery (CMA). The bihemispheric, median, and azygos ACA patterns were also identified. Results The majority (373/456, 81.8%) exhibited a typical DACA pattern. The bihemispheric, median, and azygos patterns were identified in 66/456 (14.5%), 10/456 (2.2%), and 7/456 (1.5%), respectively. The CMA was present in 824/912 (90.4%) of the hemispheres, with a trend towardmale predominance for bilateral presence (males: 167/192, 86.98%; females: 210/264, 79.55%; p = 0.05). In particular, the CMA was present significantly more frequently (p = 0.002) in the left hemispheres of male patients. Gender differences in CMA presence persisted in the analysis of the patients with a typical DACA pattern. Conclusion This study provides insights into the variations of the DACA in the Greek population. The observed gender differences in CMA rates suggest potential morphological variations in cerebral vasculature between males and females and contribute to a better understanding of vascular anatomy for clinical and surgical applications.

Quantification of Hybrid Topological Spin Textures and Their Nanoscale Fluctuations in Ferrimagnets.

Noncolinear spin textures, including chiral stripes and skyrmions, have shown great potential in spintronics. Basic configurations of spin textures are either Bloch or Néel types, and the intermediate hybrid type has rarely been reported. A major challenge in identifying hybrid spin textures is to quantitatively determine the hybrid angle, especially in ferrimagnets with weak net magnetization. Here, we develop an approach to quantify magnetic parameters, including chirality, saturation magnetization, domain wall width, and hybrid angle with sub-5 nm spatial resolution, based on Lorentz four-dimensional scanning transmission electron microscopy (Lorentz 4D-STEM). We find strong nanometer-scale variations in the hybrid angle and domain wall width within structurally and chemically homogeneous FeGd ferrimagnetic films. These variations fluctuate during different magnetization circles, revealing intrinsic local magnetization inhomogeneities. Furthermore, hybrid skyrmions can also be nucleated in FeGd films. These analyses demonstrate that the Lorentz 4D-STEM is a quantitative tool for exploring complex spin textures.

Розробка методології імплементації транзакцій в розподілених системах з мікросервісною архітектурою

The paper describes the analysis of the problems of using microservice architecture in distributed systems. Emphasis is placed on flexibility in the choice of technologies, scalability and organization of teams working on given microservices, technical and domain problems of transaction implementation in comparison with a monolithic system. The main focus is on transactions, as they ensure atomicity, consistency, isolation, and persistence across multiple services. In the process of analyzing modern approaches and solutions for working with transactions in distributed systems, it was found that one of the effective solutions is the use of the Transactional Outbox pattern. Its implementation in the form of Spring starter is presented. The latter is added to the system, configured and facilitates the use of transactions and the publication of events that are part of a transaction in a microservice architecture. The developed methodology for implementing distributed transactions based on message queues, using the above-mentioned starter, is described in detail. The basic configurations and settings of message queues for the correct operation of transactions in distributed systems are defined

Demand Driven Material Requirement Planning: Core concepts and analysis of its behavior on a case study

Demand Driven Material Requirement Planning (DDMRP) is a recent Production Planning and Control (PPC) approach. It has been mainly studied through its reported performance on specific industrial applications or through its parametrization. This article aims to analyze its main characteristics and to compare its behavior with MRP2 in an in-vitro case study. Results show that, in their basic configurations, DDMRP leads to a lower number of orders but of a larger size, and furthermore, to a slightly higher stock level (+6%) but distributed in a different way than in MRP2. Those results allow a better understanding of some strengths and weaknesses of DDMRP.

Analog CMOS Design in Nanometer Regime

There is no doubt that the short-channel effects have affected the analysis and design of modern analog CMOS integrated circuits significantly. Thus, models that take into account these effects must be adopted in order to obtain more accurate results. In this paper, the AC small-signal low-frequency equivalent circuit of the short-channel MOSFET transistor is developed using an appropriate model. The impact of short-channel effects on the operation of basic building blocks of analog integrated circuits such as basic amplifier configurations, cascode stage, differential amplifier and composite transistor is investigated quantitatively. Additionally, the nonlinear distortion is investigated using the adopted model.

SIMULATION MODELING OF MULTI-PORT DC-DC CONVERTER IN MPPT SOLAR BATTERY CONTROLLERS UNDER NEURAL NETWORK CONTROL

Photovoltaic generation system - energy system, designed to convert useful solar energy through photovoltaic systems. It can consist of several components, including a solar array, DC/DC and DC/AC semiconductor converter, battery, filter or transformer, control system (CS). Depending on the application, photovoltaic systems can be operated as part of a self-contained power plant or operate on a network. Thus, it is possible to distinguish several basic configurations of photovoltaic generation systems. The standalone generation system is the most common configuration of photovoltaic generation systems, which contains rechargeable batteries (AB). This system is completely independent of the centralized power supply networks and is suitable for comfortable energy supply to consumers. The use of AB makes it possible to increase the reliability of the photovoltaic system and to extend the possibilities of using e.g. battery power is used during insufficient light or when the load exceeds the generation of solar cells. The scope of such configurations are lighting systems of residential and non-residential objects, power supply of houses and buildings, security systems and emergency power supply, power supply of remote residential and non-residential objects, Power supply to spacecraft, etc. Autonomous generation systems typically contain two transducers. The DC/DC converter acts as a battery charge controller. The control system for such a transducer may include the function of tracking the maximum power point for the maximum use of solar energy. The excess energy will be stored in AB. The DC/AC converter converts the DC current energy into the AC energy of the required frequency and voltage. The advantage of such a system is the possibility of using solar energy, both during the day and at night, due to the power of AB and the possibility of using the system at remote sites where there is no grid power supply. The disadvantage of such a system is the loss of double conversion of solar energy and the high cost of batteries. Artificial Neural Network (ANN) provides an alternative way to solve complex problems. A neural network, with the right structure, can compute the values of any continuous function with some predetermined accuracy. The neural network requires no knowledge of the internal parameters of the solar module, learns quickly, has the ability to optimize and approximate. Therefore, the use of INS to track the maximum power point is relevant and of practical and scientific importance. Keywords: multi-port DC converter, artificial neural network (ANN), rechargeable batteries (AB), pulse width modulation (PWM), solar panels (SP), MOSFET power keys

Assessment of the Impact of Basic Public Service Facility Configuration on Social–Spatial Differentiation: Taking the Zhaomushan District of Chongqing, China

Objectively assessing the impact of various basic public service facilities on social–spatial differentiation has become a prerequisite for promoting urban social integration and development. However, in practice, the configuration of basic public service facilities is not always conducive to social integration, especially at the microscale. Effectively measuring the inhibitory or aggravating effects of various basic public service facility configurations on social–spatial differentiation has become a challenge. Based on the assumption that the configuration of basic public service facilities has inhibitory and aggravating effects on social–spatial differentiation, this study selected two types of objects: social space and basic public service facilities to refine the research elements. Using spatial and statistical analysis methods such as ecological factors, clustering, correlation, mediation, and superposition analysis, a framework was constructed to evaluate the impact of basic public service facility configuration on social–spatial differentiation and take the Zhaomushan area in Chongqing, China, as a typical case for verification. The study found that registered residence, income, employment location, and residential density are still the main factors of social–spatial differentiation in the study area. The main factors contributing to the differentiation of basic public service facilities are elderly care and housing security, public transportation and green space access, education and employment security, and small-scale medical and health facilities in the study area. In the eight principal factor pairs after the superposition of two differentiation spaces, six pairs showed weakened spatial differentiation, while two pairs showed intensified spatial differentiation. This indicates that the allocation of basic public service facilities will simultaneously inhibit and exacerbate social–spatial differentiation, but the inhibitory effect is significantly stronger than the exacerbating effect. Among them, public transportation and green parks are the main types of facilities that mainly exacerbate social–spatial differentiation. This dual effect is specifically reflected in the change in the spatial adaptation position of social space and basic public services, the weakening of the original social space differentiation boundary and the emergence of new differentiation boundaries simultaneously, and the multicenter composite form of social space. In the future, quantitative evaluation based on research frameworks can provide scientific basis for constructing spatial adaptability strategies for the supply of basic public service facilities and social production and life, such as adjusting the distribution, scale, and spatiotemporal relationship between basic public service facilities and residential communities in a reasonable manner. This is crucial for promoting social integration.

Functional requirements of patient data management systems in intensive care medicine

As part of the German government's digitization initiative, the paper-based documentation that is still present in many intensive care units is to be replaced by digital patient data management systems (PDMS). In order to simplify the implementation of such systems, standards for basic functionalities that should be part of basic configurations of PDMS would be of great value. This paper describes functional requirements for PDMS in several categories. Criteria for standardized data documentation were defined by the authors and derived functional requirements were classified into two priority categories. Overall, general technical requirements, functionalities for intensive care patient care, and additional functionalities for PDMS were defined and prioritized. Using this paper as astarting point for adiscussion about basic functionalities of PDMS, it is planned to develop and obtain consensus on definitive standards with representatives from medical societies, medical informatics and PDMS manufacture.

Opposition to Synchronization of Bistable State in Motif Configuration of Rössler Chaotic Oscillator Systems

This paper presents the study of the opposition to the synchronization of bistable chaotic oscillator systems in basic motif configurations. The following configurations were analyzed: Driver-response oscillator systems coupling, two driver oscillator systems to one response oscillator, and a three-oscillator systems ring unidirectional configuration. The study was conducted using the differential equations representing the piecewise linear Rössler-like electronic circuits; the initial conditions were changed to achieve a bistable characteristic Homoclinic H-type or Rössler R-type attractor. Analyzing a sweep of the initial conditions, the basin attractor was obtained. It can be observed that each system has a preferred Homoclinic chaotic attractor with any perturbation or change in initial conditions. A similarity analysis based on the coupling factor was also performed and found that the system has a preferentially Homoclinic chaotic attractor.

Construction of multi-loop thermodynamic cycles: Methodology and case study

Developing renewable energy and improving the efficiency of the existing energy system are effective measures to realize CO2 emission reduction. This makes the energy utilization scenario more and more complex, which leads to the energy system needing to be able to utilize multiple heat source fluids and output multiple products. Compared with single-loop thermodynamic cycles (such as the basic configurations of Organic Rankine Cycle and Brayton Cycle), multi-loop thermodynamic cycles are more suitable for such complex energy utilization scenarios because of their complexity and variability. However, there is no systematic construction method for multi-loop thermodynamic cycles in the existing studies. Therefore, a novel construction method for multi-loop thermodynamic cycles is proposed based on the mapping from closed curves to thermodynamic cycles in this study. The multi-loop thermodynamic cycle is constructed by replacing edges of the closed curve with different thermodynamic processes. The effectiveness of the proposed method is demonstrated using a test case of the double-pressure Brayton cycle and a summary of ten existing multi-loop thermodynamic cycles. The proposed method provides a new perspective for the construction of multi-loop thermodynamic cycles. This makes research on the construction of thermodynamic cycles more theoretical, which is beneficial to obtain some novel multi-loop thermodynamic cycles.

An efficient data-driven optimization framework for designing graded cellular structures

Cellular structures are increasingly applied in engineering practice since they have excellent mechanical and multifunctional properties, such as light weight, energy absorption and noise reduction. In this paper, an efficient data-driven M-VCUT (multiple variable cutting) optimization framework is developed for designing the graded cellular structures. Three main parts are included in this method, i.e., the establishment of problem-independent offline database, the coarse-scale optimization, and the geometry reconstruction of full-scale cellular structure. The advantage of this method is that: (1) it has high computational efficiency due to the establishment of a problem-independent database in an offline manner; (2) it directly adopts numerical derivation, which makes the calculation of sensitivity more convenient; (3) it has fewer design variables. Based on the proposed method, the designer can predefine a variety of different basic microstructure configurations, and then combine them into different microstructures according to different requirements, realizing the integrated design of microstructure and macrostructure. Numerical examples are carried out for verifying the validation and efficiency of the proposed method.

PhysioKit: An Open-Source, Low-Cost Physiological Computing Toolkit for Single- and Multi-User Studies.

The proliferation of physiological sensors opens new opportunities to explore interactions, conduct experiments and evaluate the user experience with continuous monitoring of bodily functions. Commercial devices, however, can be costly or limit access to raw waveform data, while low-cost sensors are efforts-intensive to setup. To address these challenges, we introduce PhysioKit, an open-source, low-cost physiological computing toolkit. PhysioKit provides a one-stop pipeline consisting of (i) a sensing and data acquisition layer that can be configured in a modular manner per research needs, and (ii) a software application layer that enables data acquisition, real-time visualization and machine learning (ML)-enabled signal quality assessment. This also supports basic visual biofeedback configurations and synchronized acquisition for co-located or remote multi-user settings. In a validation study with 16 participants, PhysioKit shows strong agreement with research-grade sensors on measuring heart rate and heart rate variability metrics data. Furthermore, we report usability survey results from 10 small-project teams (44 individual members in total) who used PhysioKit for 4-6 weeks, providing insights into its use cases and research benefits. Lastly, we discuss the extensibility and potential impact of the toolkit on the research community.