Input-output Process Research Articles

First step toward designing effective real-time control systems in laser directed energy deposition

In-process monitoring and control are essential for quality assurance and consistency of laser-based directed energy deposition processes. Detection of irregularities during deposition in terms of defects or flaws is based on in situ monitoring of output process parameters such as temperature, melt-pool geometry, or deposition height. The real-time feedback of these output parameters allows the development of control strategies for real-time adjustment of input process parameters, such as laser power or scanning speed, to correct detected deviations from the desired output process parameters. Therefore, criteria such as sensitivity, stability, correlation, trends, and interactions of the input-output process parameters have a direct impact on controller design, establishing, for example, control limits or tolerance ranges of the output parameters. This paper focuses on the study of the characteristics of output process parameters to input process parameters. This research involves analyzing and comparing the deposition of single tracks under various input process parameters, including laser power and scanning speed. Melt-pool geometry and temperature are estimated from a visual camera and a hyperspectral line camera, whereas the final deposition geometry is obtained from a laser triangulation scanner. The results show the linearity between input and output process parameters, the steadiness of the output process parameters, the relation between melt-pool and final deposition, and offer insights to design effective in-process control systems.

Dynamics, regional heterogeneity and robustness of fiscal poverty alleviation efficiency in China: dynamic network DEA and Bootstrap resampling methods

This paper aims to tackle the issues of evaluating the dynamic performance of fiscal poverty alleviation in 22 Chinese provinces (regions) over 2016–2019. First, we open up the internal structure of the fiscal poverty alleviation system (FPAS) and clarify its input-output process as a two-stage series system consisting of the public investment process and poverty reduction process. On this basis, we construct dynamic network DEA models with and without carryover activities for measuring the period efficiency and overall efficiency of FPASs (i.e., FPAS efficiency) and the period efficiency and overall efficiency of evaluation indicators (i.e., indicator efficiency), and also prove the relationship between the two proposed models. Second, we combine the proposed dynamic network DEA models and Bootstrap resampling method to assess the robustness of FPAS efficiency for exploring the risk of returning to poverty for each FPAS. The results show that: (i) the carryover activities have some impact on the FPAS efficiency and indicator efficiency; (ii) the period efficiency shows an upward trend, and most of FPASs or evaluation indicators have been at high efficiency in the sample period, but there is still regional heterogeneity; (iii) there are some differences between the indicator efficiency and there are some inconsistencies between them and the FPAS efficiency; (iv) bootstrap resampling results indicate that several FPASs have a great risk of returning to poverty.

Measuring Levels of Infrastructure Development and its Impact on Regional Growth - Insights from Indonesia

Infrastructure development is a linchpin for regional growth, especially in emerging economies like Indonesia. There have been many debates over the necessity of infrastructure investment over direct economic stimuli. This study delves into the critical role of infrastructure in shaping regional dynamics in Indonesia. We employ the Infrastructure Development Index (IDI), a composite metric amalgamating various infrastructure clusters into a singular value. A sample of strategic region in Indonesia are observed in this research, classified into urban and non-urban areas to highlight the different levels of impact the infrastructure development brings. Several regional development indicators such as: (a) economic growth; (b) poverty rate; (c) gini index; (d) human development index; and (e) unemployment rate is used to explore its relationship with infrastructure development. This research shows a nuanced pattern where mainly urban areas exhibiting higher IDI value and higher impact on its regional growth and development. While non-urban areas still experiencing lower impact due to the difficulties in infrastructure access and the disparity of access between the areas. It indicates the prevailing urban bias in infrastructure development, needing an improved urban-rural linkage on overall economic input-output processes. In sum, this study provides further insights into the pivotal role of infrastructure in regional development in Indonesia, offering a roadmap for informed decision-making in the pursuit of comprehensive and sustainable regional progress.

Driving factors and decoupling effects of agricultural carbon emissions in Jiangxi Province based on time-varying parameter C-D production function.

The reduction of agricultural emission plays an important role in realizing the dual-carbon goals. It is thus of great significance to examine the characteristics and drivers of regional agricultural carbon emission. We measured agricultural carbon emission in Jiangxi Province from the perspective of input-output and production processes, and explored the drivers and decoupling dynamics of agricultural carbon emission by using the LMDI decomposition method together with the Tapio decoupling model modified by time-varying parameter C-D production function. The results showed that agricultural carbon emission in Jiangxi increased by 26.4% from 2010 to 2021, and the carbon emission intensity decreased year by year with an average annual rate of 4.9%. Factors such as agricultural carbon intensity, labor input, and capital stock collectively reduced carbon emission by a total of 61.05 Mt, with a contribution of 27.0%, 44.5% and 28.5%, respectively. Level of agricultural economic development, agricultural structure, and technological progress had strong driving effects, which accounted for 75.7%, 5.6% and 18.8%, respectively. Agricultural carbon emission in Jiangxi was weakly decoupled from economic development, capital stock, and technological progress factors, but was negatively decoupled from labor input. Moreover, the decoupling state was more desirable in the later period than in the earlier period. Our results suggested that the application of the time-varying parameter C-D production function is innovative and applicable by incorporating technology, labor, and capital factors in the examination of carbon emission drivers and decoupling effects.

Argumentation with justified preferences

It is often necessary and reasonable to justify preferences before reasoning from them. Moreover, justifying a preference ordering is reduced to justifying the criterion that produces the ordering. This paper builds on the well-known ASPIC+ formalism to develop a model that integrates justifying qualitative preferences with reasoning from the justified preferences. We first introduce a notion of preference criterion in order to model the way in which preferences are justified by an argumentation framework. We also adapt the notion of argumentation theory to build a sequence of argumentation frameworks, in which an argumentation framework justifies preferences that are to underlie the next framework. That is, in our formalism, preferences become not only an input of an argumentation framework, but also an output of it. This kind of input-output process can be applied in the further steps of argumentation. We also explore some interesting properties of our formalism.

Heralded hyperparallel Fredkin gate with robust fidelity

We propose a heralded hyperparallel Fredkin gate for a three-photon system with the help of the optical property of a quantum dot (QD) embedded in a microcavity. This hyper-Fredkin gate performing both on spatial and polarized degrees of freedom (DoFs) of the three-photon system is equal to double independent three-photon Fredkin gate in one DoF, which has advantages over consuming a less quantum resource, accelerating calculation speed, and inhibiting photon-dissipation noise. Meanwhile, the fidelity of our hyper-Fredkin gate, in principle, approach unit even for the non-identical QD-cavity systems, as the imperfections involved in practical input–output processes of three photons can be converted into heralded errors by clicking the detectors rather than infidelity. Furthermore, the flexibility of the gate can be directly extended to construct some types of hybrid hyper-Fredkin gates with the same high fidelity and efficiency, accessibly performed under existing experimental techniques, as well as used large-scale quantum information processing.

Atypical speech production of multisyllabic words and phrases by children with developmental dyslexia.

The prevalent "core phonological deficit" model of dyslexia proposes that the reading and spelling difficulties characterizing affected children stem from prior developmental difficulties in processing speech sound structure, for example, perceiving and identifying syllable stress patterns, syllables, rhymes and phonemes. Yet spoken word production appears normal. This suggests an unexpected disconnect between speech input and speech output processes. Here we investigated the output side of this disconnect from a speech rhythm perspective by measuring the speech amplitude envelope (AE) of multisyllabic spoken phrases. The speech AE contains crucial information regarding stress patterns, speech rate, tonal contrasts and intonational information. We created a novel computerized speech copying task in which participants copied aloud familiar spoken targets like "Aladdin." Seventy-five children with and without dyslexia were tested, some of whom were also receiving an oral intervention designed to enhance multi-syllabic processing. Similarity of the child's productions to the target AE was computed using correlation and mutual information metrics. Similarity of pitch contour, another acoustic cue to speech rhythm, was used for control analyses. Children with dyslexia were significantly worse at producing the multi-syllabic targets as indexed by both similarity metrics for computing the AE. However, children with dyslexia were not different from control children in producing pitch contours. Accordingly, the spoken production of multisyllabic phrases by children with dyslexia is atypical regarding the AE. Children with dyslexia may not appear to listeners to exhibit speech production difficulties because their pitch contours are intact. RESEARCH HIGHLIGHTS: Speech production of syllable stress patterns is atypical in children with dyslexia. Children with dyslexia are significantly worse at producing the amplitude envelope of multi-syllabic targets compared to both age-matched and reading-level-matched control children. No group differences were found for pitch contour production between children with dyslexia and age-matched control children. It may be difficult to detect speech output problems in dyslexia as pitch contours are relatively accurate.

Reverse Engineering

Ever since the establishment of Translation Studies as an independent academic discipline in the 1970s, there has been an ongoing debate about the relationship between theory and practice, to which this paper aims to make a modest practical contribution in the form of a novel procedure for textual analysis and synthesis. Intellectual advances are often triggered by flashes of inspiration which suggest analogies that facilitate shifts in perception and focus that, in turn, lead to changes in understanding. What is offered here may not be a flash of inspiration but is, at least, a new analogy for the definition of translation: Translation is a kind of engineering, specifically reverse engineering. Through the lens of RE, translation redefines itself as a mental-physical, two-phase, input-output process in which texts are deconstructed (read and understood) and reconstructed (written) as new texts that resemble the originals but are not copies of them. This suggests a model of translating that recognizes the crucial role of efficient reading in the process of translating and is realized in the form of a straight-forward, simple but revealing Procedure: a mechanism for expanding the individual translator’s competence as a reader and as a writer and for sharing this increased expertise with others. The approach outlined here, Translation as Reverse Engineering (TARE), would not exist but for insights from others, in particular a specific proposal from Ali Darwish (2008) and, crucially, from the broad sweep of Hallidayan Systemic Functional Linguistics (SFL), with its view of language as purposeful social action (1978) and the more recent translation-oriented work of Munday et al. (2008, 2021). The Procedure is described in detail and is demonstrated in action in the deconstruction and potential reconstruction of three short texts. The value of the approach may lie in the way it facilitates the work of the translator and, by becoming part of his or her toolkit (to borrow Chesterman & Wagner’s 2002 term), perhaps, contributing to bridging the current gap between theory and practice.

When the Far Right Makes the News: Protest Characteristics and Media Coverage of Far-Right Mobilization in Europe

When do the media cover far-right protests? News coverage matters for the entrenchment of the far right in contemporary democracies, but little comparative research has looked at what drives news attention to far-right mobilization. We apply a classic input–output process model of news selection bias to test the hypothesis that the visibility of far-right protests events depends on the characteristics of protest initiators, type of action, and reactions. We appraise this via logistic regressions on an original dataset of 5972 protest events retrieved from online press releases by far-right groups (input) and national quality newspapers (output) in 11 European countries (2008–2018). The analysis confirms that news media are particularly responsive to contentious action, protest around migration issues, and action–reaction chains between political opponents. Our findings shed light on the role of news organizations in the success of the far-right and on the pathways by which these movements shape public agendas.

What lies behind the success of Italian GIs products? Questioning tradition in consortia via aggregated conditional efficiency

Firms and territories are considered extremely interrelated, especially approaching the market of agri-food products detaining the PDO (Protected Designation of Origin) and PGI (Protected Geographical Indication) labels. By aiming at reducing costs and simultaneously exploiting potential benefits, entrepreneurial realities often collaborate through consortia. This aspect takes on a crucial relevance when considering the Italian context, widely known for its high-quality products, the vocation to cooperate, and the high adaptability to insidious locations. In this light, this study assesses the efficiency level of in-the-consortia Italian firms by conditioning for two external factors affecting the input–output process evaluated, i.e. physical riskiness and vocation to cooperate. The Data Envelopment Analysis (DEA) scores are aggregated by using firms’ membership in the consortia as the DEA aggregation criterion. More than 600 firms aggregated in 50 consortia allow for a capillary and locally-based study over the 2011–2020 period. The study signals tips about geographical concentration and proximity since it tests whether tradition and attitude to cooperate motivate the agri-food industry efficiency level, in line with the historical regional background of these organizational forms. Finally, suggestions to exploit the market of certified products are discussed both for policy-makers and practitioners, as well as new opportunities for future research.

Warehouse Manager Selection by CRITIC-MULTIMOORA Hybrid Method based on Single-Valued Neutrosophic Sets

Warehouses are junction points in the supply chain. To avoid disruptions in the supply chain flow, the materials stored in the warehouse must be safely protected and made available for the next transportation activity. Warehouse personnel are critical in ensuring full-time material flow. For the administrative dimension, warehouse managers are the leaders responsible for the successful execution of all warehouse input-output processes. Therefore, a successful warehouse manager is needed for successful warehouse operations. The aim of this research is to determine the warehouse manager selection criteria and to select the best warehouse manager among the candidate with using multi-criteria decision making (MCDM) methods as a hybrid. In the literature, it is seen that the manager selection problem is overseen with various MCDM methods. In this study, eight warehouse manager selection criteria were determined and their weights were calculated by the criteria importance through inter-criteria correlation based on single-valued neutrosophic set method (SVNS-CRITIC) method. Four alternatives were ranked with the multi-objective optimization by ratio analysis based on single-valued neutrosophic sets (SVNS-MULTIMOORA) method. The manager selection was made for the general warehouse owned by a company operating in Turkey. A team consisting of two experts and a proficient manager was established to evaluate the candidates. As a result of the application, the most important warehouse manager selection criterion is determined as the skills of managers to manage warehouse input-output and storage activities. In addition, the best manager candidate was determined for the general warehouse. According to the results of the research, suggestions were developed for warehouse manager candidates and researchers. With this research, it has been brought to the literature that warehouse manager selection criteria and SVNS-CRITIC-MULTIMOORA hybrid method can be used in manager selection problems.

TELEMEDICINE AND ELECTRONIC HEALTH RECORD IMPLEMENTATION IN RURAL AREA: A LITERATURE REVIEW

The Indonesian Minister of Health 2019 issued regulations regarding the implementation of telemedicine services between health service facilities. Telemedicine is aimed primarily at rural areas. This research aims to look at the quality of telemedicine-based services, which are documented in an electronic health record (EHR) with complete information. This research uses the narrative literature review method: Garuda journal channels, Google Scholar, IEEE Explorer, ProQuest, PubMed, Science Direct, and Scopus. With the input-output process approach, eight scientific articles were published on countries with telemedicine/telehealth policies in rural areas. The implementation of telemedicine has advantages and disadvantages depending on the things supported and the target users. It must have policies, infrastructure, financial resources, and human resources to use, maintain and develop telemedicine. Telemedicine will help the health service process by increasing the degree of public health in rural areas if it is used on a large scale. The completeness of the EHR seems to be lacking in terms of informed consent. Still, a quality EHR can make it easier for health workers to enforce the history, establish the diagnosis, and provide patient healthcare.

Estimation of portfolio efficiency via stochastic DEA

Traditional data envelopment analysis (DEA) and diversification DEA are two common data-driven evaluation approaches, which have been widely used in the estimation of portfolio efficiency. The above two DEA approaches usually use the risk and expected return indicators to build the input-output process of portfolios. However, this input-output process derived from the risk and expected return is inconsistent with the actual investment process, since the real input should be the initial wealth, and the output should be the terminal wealth. To address this problem, we propose a novel input-output process based on the initial and terminal wealth of portfolios. We transform the terminal wealth into the rate of return and construct a stochastic attainable set by using portfolio returns. We provide three deterministic estimation approaches to deal with the stochastic attainable set, and then obtain three deterministic attainable sets. We further propose three stochastic DEA models to estimate the portfolio efficiency by using the above three deterministic attainable sets. Finally, we provide an empirical analysis to assess the portfolio efficiency of 50 open-ended funds in China. The results show that there are some differences in the portfolio efficiency and its ranking between the proposed DEA models and the existing DEA models, which further verify the rationality of the proposed DEA models.

On the control of flying qubits

The control of flying quantum bits (qubits) carried by traveling quantum fields is crucial for coherent information transmission in quantum networks. In this paper, we develop a general framework for modeling the control of flying qubits based on the quantum stochastic differential equation (QSDE) that describes the input-output process actuated by a standing quantum system. Under the continuous time-ordered photon-number basis, the infinite-dimensional QSDE is reduced to a low-dimensional deterministic differential equation for the non-unitary state evolution of the standing quantum system, and the outgoing flying-qubit states can be expressed in the form of randomly occurring quantum jumps. This makes it possible, as demonstrated by examples of flying-qubit generation and transformation, to analyze general cases when the number of excitations is not reserved. The proposed framework lays the foundation for the design of flying-qubit control systems, with which advanced control techniques can be incorporated for practical applications.

Measuring the dynamic efficiency of socially responsible investment funds: evidence from dynamic network DEA with diversification

This article proposes some alternative multi-period diversification-consistent data envelopment analysis (DEA) models to assess the dynamic performance of socially responsible investment (SRI) funds accounting for both finance and SRI criteria. First, three portfolio possibility sets (PPSs) are constructed based on some alternative dynamic input-output processes of SRI funds. Second, three diversification-consistent DEA models are developed by combining the directional distance function (DDF) measure with the proposed PPSs. Finally, this article selects 45 SRI funds to investigate the impact of social responsibility scores (SRSs), intermediate linkages, efficiency weights, and projection directions on their efficiency and ranking, respectively.

A package auto-counting model based on tailored YOLO and DeepSort techniques

In the industrial area, the deployment of deep learning models in object detection and tracking are normally too large, also, it requires appropriate trade-offs between speed and accuracy. In this paper, we present a compressed object identification model called Tailored-YOLO (T-YOLO), and builds a lighter deep neural network construction based on the T-YOLO and DeepSort. The model greatly reduces the number of parameters by tailoring the two layers of Conv and BottleneckCSP. We verify the construction by realizing the package counting during the input-output warehouse process. The theoretical analysis and experimental results show that the mean average precision (mAP) is 99.50%, the recognition accuracy of the model is 95.88%, the counting accuracy is 99.80%, and the recall is 99.15%. Compared with the YOLOv5 combined DeepSort model, the proposed optimization method ensures the accuracy of packages recognition and counting and reduces the model parameters by 11MB.

A multilayer-multiplexer network processing scheme based on the dendritic integration in a single neuron.

Advances in neuronal studies suggest that a single neuron can perform integration functions previously associated only with neuronal networks. Here, we proposed a dendritic abstraction employing a dynamic thresholding function that models the spatiotemporal dendritic integration process of a CA3 pyramidal neuron. First, we developed an input-output quantification process that considers the natural neuronal response and the full range of dendritic dynamics. We analyzed the IO curves and demonstrated that dendritic integration is branch-specific and dynamic rather than the commonly employed static nonlinearity. Second, we completed the integration model by creating a dendritic abstraction incorporating the spatiotemporal characteristics of the dendrites. Furthermore, we predicted the dendritic activity in each dendritic layer and the corresponding somatic firing activity by employing the dendritic abstraction in a multilayer-multiplexer information processing scheme comparable to a neuronal network. The subthreshold activity influences the suprathreshold regions via its dynamic threshold, a parameter that is dependent not only on the driving force but also on the number of activated synapses along the dendritic branch. An individual dendritic branch performs multiple integration modes by shifting from supralinear to linear then to sublinear. The abstraction includes synaptic input location-dependent voltage delay and decay, time-dependent linear summation, and dynamic thresholding function. The proposed dendritic abstraction can be used to create multilayer-multiplexer neurons that consider the spatiotemporal properties of the dendrites and with greater computational capacity than the conventional schemes.

Decoupling of economic growth from CO2 emissions in Yangtze River Economic Belt sectors: A sectoral correlation effects perspective

For making clear decoupling state of sector economic growth from CO2 emissions in the input–output process, in this paper, we firstly explore the correlation effects of sector CO2 emissions by defining it as comprehensive effects of sector CO2 emissions from fossil energy consumption in the initial input, intermediate products, final products and circular correlation of the input–output process, and decomposing it into direct effect, full effect, Spreading effect and sensitive effect. Then we set up a methodology of correlation effects decoupling index to discover their decoupling status and sources. Finally, we concretely investigate the breakthrough points of sector CO2 emissions reduction in the case study of the Yangtze River Economic Belt (the YREB) sectors of China. The results show: (1) Correlation effects of CO2 emissions is higher in the YREB energy-intensive sectors. (2) The YREB sectors of decoupling of economic growth from CO2 emissions decreases obviously from 89.7% to 62.1% from 2007–2012 to 2013–2017, which is impacted by decoupling deterioration of correlation effects of CO2 emissions in the energy-intensive sectors. (3) The YREB key sectors of CO2 emissions reduction are the energy-intensive sectors with focus on the parts of decoupling deterioration of correlation effects of sector CO2 emissions. The proposed analysis framework is efficient for analyzing decoupling of correlation effects of CO2 emissions in the YREB sectors of China, and can also be applied to similar analysis and extended to multi-regional analysis.

Seed bank persistence of artificial vegetation under stochastic shock in desert regions

Seed bank persistence plays a significant role in maintaining the sustainability of artificial vegetation in desert regions. However, the periods of droughts after each rainfall event form a series of stochastic shocks and result in depletion of the seed bank. Understanding seed bank persistence under stochastic shocks is a crucial prerequisite to evaluation of the sustainability of artificial vegetation under ongoing drought, but few studies have addressed the response of soil seed bank persistence to frequent stochastic shocks in deserts. In this paper, a stochastic shock model describing the input–output process of the seed bank is proposed based on modern risk theory to explore seed bank persistence of artificial vegetation in desert regions. The existence condition of the seed bank and the lower bound of the probability of seed bank persistence under stochastic shock after a long time were theoretically determined. As a verification of the theoretical model, seed bank persistence of artificial sand-binding vegetation on the southeastern margin of the Tengger Desert in China was investigated based on field observation and experimental and empirical data. The numerical results reveal that the seed bank of artificial sand-binding vegetation will always exist under stochastic shocks with a probability greater than 95%, suggesting that in the long-term succession process the current artificial sand-binding vegetation will likely maintain the development trend toward the adjacent natural vegetation.

Control of TITO processes using sliding mode controller tuned by ITAE minimizing criterion based Nelder-Mead algorithm

Abstract Control of multi input and multi output (MIMO) process with interaction is often encountered in process industry. Such MIMO processes are controlled using conventional sliding mode controller (SMC) and tuned by integral square error (ISE) minimizing criterion based Nelder-Mead algorithm. SMC tuned by integral time absolute error (ITAE) minimization criterion based Nelder-Mead algorithm is proposed in this work. Three categories of two inputs and two outputs (TITO) process models are represented in the matrix form, with each of the matrix element representing a first order plus dead time (FOPDT) process. These TITO models are categorized based on the ratio ε, between dead time and time constant of the FOPDT model which forms the matrix element of the TITO model. The performance of conventional SMC is evaluated for these three categories of TITO models, in which the TITO process models with the ratio ε greater than the one, exhibited by poor closed loop performance, whereas the proposed SMC when applied to the these process models delivered superior closed loop performance.