Concept Of Matching Research Articles

Matching in practice: how to find the right family foster home for the right child

The concept of matching refers to the process of selecting a family foster home to fit an individual child in placement. Matching is important for the quality of care, as the carers need the necessary resources to meet the child’s needs. Failure in matching can have negative consequences, such as a ‘breakdown’. The aim of this article is to explore the social workers’ practice when matching children and foster carers to ensure the children will receive good care and avoid a placement change. The article uses a qualitative approach and is based on interviews with 31 participants. Social workers and managers at municipal social services, as well as consultants, were interviewed about their work. The professionals reflected on what aspects they perceive as most important in matching and what challenges they encounter that complicate the process. Narratives of successful matches often focused on the characteristics, competence and experience of the foster carers to meet the needs of the children. Some of the challenges highlighted were time pressure and a lack of family foster homes to choose from. This means that professionals have to compromise and prioritise what is most important in relation to the needs of the child.

Transcending Individual Traditions: Zhang Taiyan’s Interpretation of Zhuangzi’s Notion of Chengxin

This article examines the nuanced interpretations of chengxin 成心 in the Zhuangzi 莊子, a foundational Daoist text, across different philosophical traditions. Historically, Daoist thinkers like Guo Xiang 郭象 and Cheng Xuanying 成玄英, along with Neo-Confucian scholars such as Lü Huiqing 吕惠卿 and Lin Xiyi 林希逸, have provided differing perspectives on the notion of chengxin. They regard it as either a source of subjective bias or an expression of heavenly principle. The core focus of this study is Zhang Taiyan’s 章太炎 innovative interpretation of chengxin as seeds (bijas) within ālaya-vijñāna (storehouse consciousness), integrating Yogācāra Buddhist concepts with traditional Daoist philosophy. The study conducts a textual analysis of Zhang’s Qiwulun Shi 齊物論釋, comparing his interpretation with earlier commentaries on the Zhuangzi. It is argued that Zhang’s approach is profoundly influenced by the Buddhist doctrine of non-duality, which underscores the interconnectedness of all phenomena. While Zhang’s interpretation has faced criticism from contemporaries and later philosophers for misunderstandings of Yogācāra theory and Kantian philosophy, it employs the method of geyi 格義 (matching concepts), not to impose one tradition over another, but to foster a dialogical process where the insights from each tradition mutually inform and transform one another. This article highlights the interpretative openness of the Zhuangzi, which invites diverse interpretations, and demonstrates how Zhang’s approach enriches this tradition by synthesizing various philosophical and religious frameworks. Zhang’s methodology remains relevant, fostering cross-cultural and inclusive philosophical dialog.

Adaptive Matching of Discrete Antenna Tuning Units of High Frequency Band to Varying Load Impedance

The issue of matching the antenna with thetransmitter-receiverplays a primary role in radio communications. The matching problem is relevant for different ranges and is solved in many ways. In the high frequency wave range, matching has a number of features when using an antenna coupler based on discrete elements consisting of capacitance and inductance boxes. The article discusses the concept of fast matching of high-frequency amplifying paths ofdecametric wavestransceivers with non-stationary loads using discrete antenna couplers. An innovative approach has been developed to the tuning process when changing the operating frequency and ensuring self-adaptation of the antenna coupler when changing the impedance, based on methods for quickly searching for the geometric proximity of points. A quick method for configuring the antenna coupler is proposed, eliminating the procedure for recalculating the input impedance based on the results of measuring the input impedance of the antenna coupler. When using it, the speed of setting the antenna coupler at the current operating frequency is limited only by the time of a single state change of the discrete power circuit, which in the case of electromagnetic relays is numerically equal to their switching time. The configuration of the antenna coupler using the method of fast search for the geometric proximity of points is based on a set of frequency cards with settings options. Such cards can be recalculated for the reference plane between the generator and the antenna coupler input for all combinations of discrete elements in accordance with the known matrix model of a discrete power circuit. This eliminates the complicated procedure of recalculating the input impedance of the antenna using complex numbers. The technical result of the proposed innovative method of antenna coupler configuringis simplification, tracking of systematic errors of the impedance meter, elimination of time-consuming calculations with complex numbers, expansion of the method functionality, reduction of the tuning duration and improvement its quality. The practical significance lies in the fact that the implementation of the proposed technical solutions in the high frequency range communications means can significantly (about 100 times) limit the duration of preparation for a radio communication session, eliminate the procedure for recalculating the antenna input impedance and reduce the resource requirements of switching elements.

Lattice matching strategy in Cu-based oxides for large-scale and long-term thermochemical energy storage

Redox-active metal oxides, particularly Cu-based oxide, are noteworthy for their economic feasibility and potential as a recyclable, zero-carbon energy source. These materials are poised to serve as a sustainable solution for large-scale and long-term thermochemical energy storage (TCES), thereby mitigating the intermittency challenges inherent in renewable energy systems. However, a significant impediment to their performance is the materials sintering at elevated temperatures, which precipitate a decline in cyclic reversibility, often manifesting even within the initial cycle of operation. To counteract this limitation, we proposed an innovative approach that leverages the concept of lattice matching, augmented by the incorporation of cigarette butts in the synthesis process to fabricate a Cu-Ce heterogeneous interface. This matched lattice preserved the integrity of the TCES material's porous architecture. Additionally, the lattice oxygen within this composite exhibits a transferability. Even after a prolonged period of two years under ambient air conditions, the TCES material retains the capacity to discharge a remarkable 99.4 % of its adsorbed energy. Furthermore, over the course of 600 cycles, the system's stability is remarkably preserved at 98–100 %, and reversible loss of pure CuO is ∼40 % within the initial cycle. Given these attributes, this TCES material emerges as a promising candidate for industrial applications.

CO2 sensing via periodic Array of graphene disks

This work aims to introduce a gas detection structure based on stacked layers of graphene-spacer-metal. The presented structure consists of three stacked layers. The first layer is the periodic arrays of graphene disks on top of a typical dielectric such as TOPAS or KAPTON with a known refractive index. Then the second layer provides an air gap opening room for a sample environment. Finally, the third layer includes the dielectric and a continuous graphene sheet. All the exploited elements are modeled by circuit element while the equivalent impedance of the whole structure is calculated. The impedance matching concept is also exploited to obtain absorption power based on the calculated impedance. Additionally, full-wave simulation is performed to investigate the circuit modeling accuracy. Achieving a perfect match for absorption versus frequency verifies the developed method's robustness. Furthermore, comprehensive and ample simulation results are reported to highlight the sensitivity and reliability of the proposed gas detector.

Maximizing energy transfer of solar-battery charge controller using voltage balancing strategy

Off-grid and grid-connected photovoltaic (PV) systems with battery storage rely heavily on efficient energy transfer to maximize PV power utilization and battery lifespan. However, existing literature often overlooks the crucial role of energy transfer efficiency in these systems. This paper proposes a novel, fundamental-based PV power flow strategy that addresses this gap by employing a concept of source-load voltage matching. The proposed strategy ensures optimal voltage matching between the PV array and the battery bank. This is achieved by configuring the battery bank voltage range (between nominal and fully charged states) to closely align with the variation in PV voltage at its Maximum Power Point (MPP) across different operating temperatures. This systematic approach requires specifying the DC load voltage, configuring the battery bank, and selecting PV modules with compatible Vmp (voltage at maximum power) parameters. The system utilizes a high-current blocking diode and current limiter for safe connection between the PV array and battery bank. Additionally, the strategy protects against battery overcharge by controlling parallel fans used for PV panel cooling. Experimental results with a 1.62 kW PV system employing lead-acid batteries demonstrate improved efficiency compared to traditional methods. This innovative approach has the potential to significantly enhance energy transfer efficiency, contributing to improved energy sustainability in PV systems.

Complex optical systems for individualized correction of presbyopia

Amultitude of available intraocular lens (IOL) models enable apersonalized approach to presbyopia correction in order to meet each patient's needs. This review article discusses more complex approaches which can be useful in selected cases. The concept of reversible trifocality enables correction of presbyopia using asupplementary intraocular lens (IOL), which can be removed if necessary (e.g., intolerance to multifocal optics). The use of capsulotomy-fixated IOLs enables high precision for positioning of the lens and better stability compared to conventional capsular bag-fixated IOLs, which can be particularly advantageous in multifocal optics. The mix and match concept enables acombination of different IOLs with various optical principles to achieve the desired binocular effect. Binocular IOL systems, which consist of two complementary IOLs, can be seen as afurther development of the mix and match concept. Knowledge of the available options and their application can further improve correction of presbyopia.

Permutation Strategies for Inference in ANOVA‐Based Models for Nonorthogonal Designs Including Continuous Covariates

ABSTRACTAnalysis of variance and linear models is undoubtedly one of the most useful statistical contributions to experimental and observational science. With the ability to characterize a system through multivariate responses, these methods have emerged to be general tools regardless of response dimensionality. Contemporary methods for establishing statistical inference, such as ANOVA simultaneous component analysis (ASCA), are based on Monte Carlo sampling; however, a flat uniform resampling scheme may violate the structure of the uncertainty for unbalanced designs as well as for observational data. In this work, we provide permutation strategies for inferential testing for unbalanced designs including interaction models and establish nonuniform randomization based on the concept of propensity score matching. Lastly, we provide a general method for modelling continuous covariates based on kernel smoothers. All methods are characterized on their ability to provide unbiased Type I error results.

Incremental-based YoloV3 model with hyper-parameter optimization for product image classification in E-commerce sector

Over the past few years, the E-commerce industry has grown tremendously for selling products to consumers. Here, the consumer can easily purchase the products from their residing seats and gets the products at the door step. Also, the image quality is suggested and also the image classification is intruded to meet the consumer prerequisite. Most of the image classification models are developed by machine learning approaches to improve the reliability, scalability, and accuracy level. Due to the heterogeneous nature of images, it restricts the features and lengthy dimensions for datasets which it degrades the performance whereas the classification of products becomes a cumbersome situation. In order to resolve the problem raised by existing methods, a novel product image classification model is proposed for the fashion E-commerce sector. The prime aspect of the proposed model is to build an effective E-commerce sector for a layman, where every individual can purchase the products appropriately. Initially, the dataset is constructed with diverse product images that are obtained from different E-commerce fields with various classes. Consequently, a novel Incremental-based Improved YoloV3 with Hyper-parameter Optimization (II-Yolov3-HO) model is introduced to enhance the classification performance. In the proposed model, some of the hyper parameters like convolution and pooling layers are replaced with the Visual Geometry Group16 (VGG16) model, the remaining convolutional layers are enhanced by the atrous convolution operation, and pooling layers are modified with Atrous Spatial Pyramid Pooling (ASPP). In entire architecture, the weight factor is optimized using Predator-based Squirrel Search Algorithm (PDP-SSA) algorithm. Thus, the new E-commerce sector becomes free to categorize the products, and if it deals with a new product, it is declared as unknown data, which is then trained again in the proposed model. Hence, the concept of classification score matching with the threshold value is accomplished to deal the untrained product and the training weight is updated optimally using the proposed PDP-SSA. Finally, the enhanced model is compared over the state-of-the-art classification, provides the expected result for significantly classifying the multiple classes of products. The developed PDP-SSA-II-YoloV3-HO model is also able to perform recommendations in E-commerce sites even when the input is given as images other than text for searching the items. These uploaded images are analyzed in the developed II-Yolov3-HO model for providing the relevant items to the customer based on their features. The developed PDP-SSA-II-YoloV3-HO model achieves 99.46 % regarding accuracy. Throughout the validation, the developed model outperforms enhanced and reliable performance than the existing approaches.

Prerequisites-based course recommendation: recommending learning objects using concept prerequisites and metadata matching

The recommendation is an active area of scientific research; it is also a challenging and fundamental problem in online education. However, classical recommender systems usually suffer from item cold-start issues. Besides, unlike other fields like e-commerce or entertainment, e-learning recommendations must ensure that learners have the adequate background knowledge to cognitively receive the recommended learning objects. For that reason, when designing an efficient e-learning recommendation method, these challenges should be considered. To address those issues, in this paper, we first propose extracting pairs concept prerequisites using Linked Open Data (LOD). Then, we evaluate the proposed list of prerequisite relationships using machine learning predictive models. Then, we present the recommendation approach based on matching concept’s prerequisites relation and courses metadata through a similarity score. The experimental result of prerequisite identification was evaluated using four well-known machine learning algorithms while achieving an accuracy of 90%. Moreover, using three known evaluation metrics, the final prerequisite-based recommendation demonstrates very good results (NDCG@10 = 86%). This solution will enhance recommendations on online learning platforms. Additionally, it will overcome the cold-start issue and accomplish the needed prerequisites and background knowledge for learners to attain their learning objectives.

Stable container-route matching in multimodal transport: A case of Yangtze River Economic Belt

Multimodal transport is promoted along the Yangtze River Economic Belt to facilitate transport between rivers and seas. This paper introduces a container-route matching problem with choice behavior in multimodal transport of the Yangtze River Economic Belt. The concept of stable matching is used to assign containers to multimodal routes in which shippers have preferences over multimodal routes and multimodal routes have preferences over shipment groups. The preference is formed as a combination of self-preference regarding freight rates and transport time, and other-preference regarding cooperation. A stable container-route matching model is formulated to tailor the non-independent preferences of shippers and route operators. A local search algorithm is designed to solve the stable container-route matching problem. The multimodal transport along the Yangtze River Economic Belt including river-sea combined transport, river-sea transport and rail-sea combined transport is used to validate the proposed model. Extensive computational experiments show that it costs to keep the cooperative relationship to avoid the risks from market fluctuations. When shipments of cooperative partners need to be transported, the total capacity utilization of routes reduces by 26 %. For high-value cargo and time-sensitive cargo, the time preference of shippers has a greater impact than the freight preference. River-sea transport is more competitive than rail-sea combined transport.

Stability analysis of interval type-2 sampled-data polynomial fuzzy-model-based control system with a switching control scheme

The stability of an interval type-2 (IT2) sampled-data (SD) polynomial fuzzy-model-based control system with a switching control scheme is studied in this paper. The uncertain nonlinear plant is depicted via an IT2 polynomial fuzzy model. To realize control, a switching IT2SD polynomial fuzzy controller is generated. This paper adopts a switching control scheme with a variable sampling period. The modeling domain consists of several sub-domains, and each sub-domain corresponds to a local IT2SD polynomial fuzzy controller. These local IT2SD polynomial fuzzy controllers form the switching IT2SD polynomial fuzzy controller. To aid in the stability analysis, this paper adopts a looped-functional-based technique. The imperfect premise matching concept is brought in to solve the mismatch dilemma caused by the SD control strategy and uncertainties. For decreasing the conservativeness, this paper takes into account the state information as well as the information of IT2 membership functions. The stability analysis is performed for each sub-domain, providing the potential for further relaxation. As polynomials exist in the stability conditions, this paper employs the sum-of-squares method for the stability investigation. The simulation outcomes confirm the efficacy of the proposed method.

Delta-band Activity Underlies Referential Meaning Representation during Pronoun Resolution.

Human language offers a variety of ways to create meaning, one of which is referring to entities, objects, or events in the world. One such meaning maker is understanding to whom or to what a pronoun in a discourse refers to. To understand a pronoun, the brain must access matching entities or concepts that have been encoded in memory from previous linguistic context. Models of language processing propose that internally stored linguistic concepts, accessed via exogenous cues such as phonological input of a word, are represented as (a)synchronous activities across a population of neurons active at specific frequency bands. Converging evidence suggests that delta band activity (1-3 Hz) is involved in temporal and representational integration during sentence processing. Moreover, recent advances in the neurobiology of memory suggest that recollection engages neural dynamics similar to those which occurred during memory encoding. Integrating from these two research lines, we here tested the hypothesis that neural dynamic patterns, especially in delta frequency range, underlying referential meaning representation, would be reinstated during pronoun resolution. By leveraging neural decoding techniques (i.e., representational similarity analysis) on a magnetoencephalogram data set acquired during a naturalistic story-listening task, we provide evidence that delta-band activity underlies referential meaning representation. Our findings suggest that, during spoken language comprehension, endogenous linguistic representations such as referential concepts may be proactively retrieved and represented via activation of their underlying dynamic neural patterns.

Peer Neighborhood Mechanisms: A Framework for Mechanism Generalization

Peer prediction incentive mechanisms for crowdsourcing are generally limited to eliciting samples from categorical distributions. Prior work on extending peer prediction to arbitrary distributions has largely relied on assumptions on the structures of the distributions or known properties of the data providers. We introduce a novel class of incentive mechanisms that extend peer prediction mechanisms to arbitrary distributions by replacing the notion of an exact match with a concept of neighborhood matching. We present conditions on the belief updates of the data providers that guarantee incentive-compatibility for rational data providers, and admit a broad class of possible reasonable updates.

Ultra-broadband and ultra-high conversion efficiency difference frequency generation in a dual-layer thin-film LiNbO3 waveguide with reversed ferroelectric domain orientations

Although there is a great breakthrough in second harmonic generation based on the birefringence and quasi phase matching (QPM) concepts, the development of an efficient difference frequency generation (DFG) based on modal phase matching (MPM) is still in its infancy at present. In this paper, we propose an ultra-broadband and ultra-high conversion efficiency mid-infrared DFG on the basis of MPM in a dual-layer waveguide consisting of two reversed poled LiNbO3 thin-films on sapphire. The ultra-high conversion efficiency is ascribed to significantly enhanced nonlinear interaction realized by making use of spatial profile of optical nonlinearity of LN crystal produced by two reversed ferroelectric domain orientations in the dual-layer waveguide. The proposed DFG device has been modeled on the basis of a 0.98 μm pump wave and a 1.34–1.44 μm signal wave, the frequency difference of which generates a mid-infrared idler wave centered at 3.32 μm wavelength. The results show that the device exhibits excellent DFG performance, including an ultra-high nonlinear conversion efficiency 434.6 % W−1 cm−2 and an ultra-broad tuning band 340 nm meanwhile, which far exceed the performance of conventional MPM devices, even the QPM ones.

An ultra-thin meta-material including graphene patterns: Coupling application

Here a novel ultra-thin meta-material structure is proposed, including periodic arrays of graphene rings, disks, and ribbons and SiO2 dielectric as spacer between graphene patterns layers at the terahertz (THz) range. The introduced device can couple electromagnetic waves by considering reflection and transmission channels as outputs. Electromagnetic wave coupling depends on the parameters design and the device thickness. The proposed structure can couple electromagnetic waves in multi-band and close frequencies including 2 THz, 4 THz, 6 THz, 7.5 THz, and 9.5 THz. By considering the impedance matching concept, an equivalent circuit model (ECM) is developed for the proposed meta-material. Also, the device stability is investigated in various physical coefficients, geometrical parameters, and incident wave angles to ensure optical applications such as sensors, indoor communications, security, and medical imaging.

Players or Pawns? University Response to the Introduction of Plan S

The European Plan S initiative intending to transform the field of academic publishing towards open access has been received with both enthusiasm and criticism. This article reflects on this case as an example of how policymaking in ‘the Europe of Knowledge’ – characterized by increasing complexity caused by problems of multi-level coordination, combined with multi-actor divergence of norms, ideas, and interests − affects and triggers university responses. The analysis of response to this initiative for reform of scientific publishing takes the concept of normative match and mismatch as its theoretical point of departure, and the article provides an overview of how Plan S has been implemented in Norwegian higher education, where the challenge for universities has been to find a balance between responding to political expectations and expectations from societal and academic stakeholders. Our findings suggest a normative mismatch related to the Plan S initiative. The article argues that the university level was left with the task of defending the academic freedom of the individual scholar, while also being delegated the responsibility of controlling the rising costs of publishing services. As a result, issues relating to academic publishing are currently of strategic interest to universities.

A Semantics-enhanced Topic Modelling Technique: Semantic-LDA

Topic modelling is a beneficial technique used to discover latent topics in text collections. But to correctly understand the text content and generate a meaningful topic list, semantics are important. By ignoring semantics, that is, not attempting to grasp the meaning of the words, most of the existing topic modelling approaches can generate some meaningless topic words. Even existing semantic-based approaches usually interpret the meanings of words without considering the context and related words. In this article, we introduce a semantic-based topic model called semantic-LDA that captures the semantics of words in a text collection using concepts from an external ontology. A new method is introduced to identify and quantify the concept–word relationships based on matching words from the input text collection with concepts from an ontology without using pre-calculated values from the ontology that quantify the relationships between the words and concepts. These pre-calculated values may not reflect the actual relationships between words and concepts for the input collection, because they are derived from datasets used to build the ontology rather than from the input collection itself. Instead, quantifying the relationship based on the word distribution in the input collection is more realistic and beneficial in the semantic capture process. Furthermore, an ambiguity handling mechanism is introduced to interpret the unmatched words, that is, words for which there are no matching concepts in the ontology. Thus, this article makes a significant contribution by introducing a semantic-based topic model that calculates the word–concept relationships directly from the input text collection. The proposed semantic-based topic model and an enhanced version with the disambiguation mechanism were evaluated against a set of state-of-the-art systems, and our approaches outperformed the baseline systems in both topic quality and information filtering evaluations.

An optoelectronic Coupler based on graphene patterns and SU-8 photoresist

PurposeThe purpose of this research is to efficiently separate incident terahertz (THz) waves into distinct transmission and reflection channels by minimizing the absorption ratio. So, the optical systems operating within the THz frequency range can developed. To achieve a multi-band response, four different periodic arrays of graphene patterns are used. These arrays are strategically stacked on both sides of three SU-8 photoresists, serving as dielectric materials. Consequently, each layer exhibits a unique influence on the device's response, and by applying four external bias voltages, the behavior of the device can be precisely controlled and adjusted.Design/methodology/approachA novel optoelectronic device operating in the THz frequency range is introduced, using periodic arrays of graphene patterns and SU-8 photoresist dielectrics. The design of this device is based on meta-surface principles, using both the equivalent circuit model (ECM) and transmission line concept. The output of the device is a THz coupler implemented by analyzing the reflection and transmission channels. The structure is characterized using the ECM and validated through comprehensive full-wave simulations. By representing the electromagnetic phenomenon with passive circuit elements, enabling the calculation of absorption, reflection and transmission through the application of the theory of maximum power transfer.FindingsBased on simulation results and theoretical analysis, the proposed device exhibits sensitivity to gate biasing, enabling efficient reflection and transmission of THz waves. The device achieves reflection and transmission peaks exceeding across the five distinct THz bands 90%, and its behavior can be tuned by external gate biasing. Moreover, the device's sensitivity to variations in geometrical parameters and chemical potentials demonstrates its reliable performance. With its outstanding performance, this high-performance meta-surface emerges as an ideal candidate for fundamental building blocks in larger optical systems, including sensors and detectors, operating within the THz frequency band.Originality/valueThe proposed device covers a significant portion of the THz gap through the provision of five adjustable peaks for reflection and transmission channels. Additionally, the ECM and impedance matching concept offers a simplified and time-efficient approach to designing the meta-surface. Leveraging this approach, the proposed device is effectively represented using passive circuit elements such as inductors, capacitors and resistors, while its performance is validated through the utilization of the finite element method (FEM) as a full-wave simulation tool. This combination of circuit modeling and FEM simulation contributes to the robustness and accuracy of the device's performance evaluation.

Structural optimization design of semi-rigid base asphalt pavement using modulus matching criterion and multi-indicator range analysis

Damage to semi-rigid base asphalt pavement is related to improper matching of the pavement structure moduli. This study mainly focused on the modulus matching of structural layers and the development of a pavement structure optimization method. First, the modulus loss of existing pavement structures was analysed, and a three-dimensional finite element model was established based on the existing pavement. Second, the influence of the modulus of each structural layer on the mechanical response indicators and fatigue life was analysed. Based on the results, a pavement structure design method using the smoothness of the stress-strain curve as the modulus matching criterion of the structural layers was proposed. And it was found that a strain convex point was present and that the stress mutation between the structural layers was significant when the modulus matching of the pavement structure was reasonable. Further, the evaluation indicators were divided into two groups, namely, mechanical indicators and fatigue life indicators. And it was proposed an optimized pavement structure design method based on modulus matching and multi-indicator range analysis. Finally, the optimal modulus combination of pavement structure was determined by this method. The research systematically studied the influence of the modulus of each structural layer on the mechanical response and fatigue life of the pavement, and proposed the concept and specific executive criteria of modulus matching for the first time. Meanwhile, it also provided an effective optimization method for pavement structure design.