Related Constraints Research Articles

Optimization Method for Center Frequency Accuracy of High-Channel-Count Arrayed Waveguide Grating in Dense Wavelength Division Multiplexing Systems

The arrayed waveguide grating (AWG) is an essential component in dense wavelength division multiplexing (DWDM) systems. With advancements in optical communication technology, the number of AWG output channels has rapidly increased. However, achieving high center frequency accuracy (CFA) for these channels has become a significant challenge. This paper presents a design and optimization approach for a high-channel-count AWG based on the silica platform and the finite difference beam propagation method (FD-BPM). The causes of center frequency deviation are analyzed, and an optimization method is proposed to adjust the constraint relationship and geometric position of the output waveguides in order to improve CFA. Simulation results demonstrate the excellent optical performance of the designed AWG, achieving a CFA of up to 0.04 times the output channel frequency spacing. The insertion loss, insertion loss uniformity, and adjacent output channel crosstalk are simulated as 1.51 dB, 0.38 dB, and 23.81 dB, respectively. The optimized CFA could compensate for center frequency deviations caused by manufacturing errors and temperature fluctuations. The findings of this research hold potential for extending the optimization to other material platforms and contributing to the development of DWDM systems in the field of optical communication.

Conformal Geometric Algebra–Based Geometric Modeling Method for Forward Displacement Analysis of 6-4 Stewart Platforms

Abstract This paper presents a novel geometric modeling method for direct displacement analysis of 6-4 Stewart platforms based on conformal geometric algebra (CGA). First, a geometric constraint relationship of four lines and a plane intersecting at a point is published. Second, a new coordinate-invariant geometric constraint equation of 6-4 Stewart platforms is deduced by CGA operation. Third, five polynomial equations are established by CGA theory. Fourth, based on the above six equations, a 5 × 5 Sylvester’s matrix is formulated by using Sylvester’s Dialytic elimination method and Gröbner bases method under the graded reverse lexicographical order. Finally, the coordinates of four points on the moving platform are revealed. Besides, a numerical example is used to prove the validity of the proposed method. The novelty of this study is that a whole geometric modeling method by geometric constraint relationship of four lines and a plane intersecting at a point is put forward under the CGA framework, which has good intuition and offers a novel idea for solving the other complex mechanisms. At the same time, Sylvester’s matrix constructed by this method is the smallest one in the known literature for forward displacement analysis of 6-4 Stewart platforms.

Grid ancillary services using electrolyzer-Based power-to-Gas systems with increasing renewable penetration

Increasing penetrations of renewable-based generation have led to a decrease in the bulk power system inertia and an increase in intermittency and uncertainty in generation. Energy storage is considered to be an important factor to help manage renewable energy generation at greater penetrations. Hydrogen is a viable long-term storage alternative. This paper analyzes and presents use cases for leveraging electrolyzer-based power-to-gas systems for electric grid support. The paper also discusses some grid services that may favor the use of hydrogen-based storage over other forms such as battery energy storage. Real-time controls are developed, implemented and demonstrated using a power-hardware-in-the-loop(PHIL) setup with a 225-kW proton-exchange-membrane electrolyzer stack. These controls demonstrate frequency and voltage support for the grid for different levels of renewable penetration (0%, 25%, and 50%). A comparison of the results shows the changes in respective frequencies and voltages as seen as different buses as a result of support from the electrolyzers and notes the impact on hydrogen production as a result of grid support. Finally, the paper discusses the practical nuances of implementing the tests with physical hardware, such as inverter/electrolyzer efficiency, as well as the related constraints and opportunities.

Stability of nonlinear impulsive systems with non-uniformly distributed packet loss

This study focuses mainly on the stability of a class of nonlinear systems with impulsive disturbance. In particular, we consider the possible non-uniformly distributed packet loss phenomenon in the controller-to-actuator channel. This packet loss is described by a characterization scenario in the average sense, known as the average packet loss interval (APLI). In this scenario, an average allocation strategy between the number of impulsive sampling intervals and the length of packet loss intervals is established. This implies that the limitations on the proportion or the upper bound of packet loss intervals can be relaxed. A sampled-data control is put forward based on impulsive disturbance, which not only brings better control performance but also reduces conservatism. In view of the Halanay inequality, the number of subsystem switchings caused by packet loss is allowed to be arbitrary. Based on the elastic constraint relationships established between system parameters and APLI, a series of conditions guaranteeing the globally uniformly exponential stability (GUES) are provided. Further, the admissible packet loss intervals can be estimated on an average basis by solving an algebraic inequality. Finally, a numerical example is discussed to demonstrate the validity of our study.

Examining the role of heritage-destination attributes on travel constraints and revisit intention using multilevel analysis

PurposeThis study aimed to explore how the attributes of heritage destinations become constraints on tourists' intention to revisit these destinations and to provide stakeholders with strategies to mitigate travel constraints, thereby increasing tourists' revisit intention.Design/methodology/approachA quantitative research approach was used, and data collection utilised a convenience sampling method. A total of 1,250 tourists completed self-administered, on-site surveys. To analyse the collected data effectively and to test hypotheses, multilevel analysis models were created.FindingsHeritage-destination attributes are found to mediate the impact of perceived constraints on tourists' intention to revisit heritage destinations. Positive perceptions of heritage and cultural attractions among tourists can mitigate the adverse effects of constraints on their intentions.Research limitations/implicationsThis study only focused on examining the downward cross-level impact, i.e. from the macro level to the individual level. This could be beneficial for exploring an upward cross-level impact.Practical implicationsThe findings provide strategic guidance for marketing programs to enhance the reputation of heritage destinations. By identifying and establishing attributes specific to heritage destinations that visitors perceive as the most appealing, program designers can effectively target their efforts. Additionally, the findings help stakeholders of heritage destinations develop and provide suitable heritage and cultural attractions and tourism infrastructure in line with tourists' preferences.Originality/valueThis study employed a multilevel approach to examine how heritage-destination attributes and related constraints on travelling on impact individuals' intentions to revisit destinations. The study considered a macro-based perspective to analyse these effects.

Financial constraints and carbon emissions: an empirical investigation

PurposeThis study aims to empirically examine the influence of financial constraints on firm carbon emissions. In addition to the role of financial constraints in firm-level carbon emissions, this study also examines this influence in the presence of governance, environmental orientation and firm-level attributes.Design/methodology/approachUsing pooled ordinary least square, this study examines the impact of financial constraints on firm-level carbon emissions using a panel of 1,536 US firm-year observations from 2008 to 2019. This study also used two-step generalized method of moment–based dynamic panel data and two-stage least square approaches to address potential endogeneity. The results are robust to endogeneity and collinearity issues.FindingsThe results suggest that financial constraints enhance the carbon emissions of the firms. The economic significance of financial constraints on carbon emissions is more pronounced for the firms that do not report environment-related expenditure investment and those that are highly leveraged. The authors further document that firms with a nondiverse gender board signify a statistically significant impact of financial constraints on carbon emissions. These results are also economically significant, as one standard deviation increase in financial constraints is associated with a 3.340% increase in carbon emissions at the firm level.Research limitations/implicationsSome implicit and explicit factors like corporate emissions policy and culture may condition the relationship of financial constraints with carbon emissions. Therefore, it would be worthwhile to consider these factors for future research. In addition, it is beneficial to identify the thresholds and/or quantiles at which financial constraints may significantly make a difference in enhancing carbon emissions.Practical implicationsThe findings offer policy implications for investment in stakeholder engagement for capital acquisitions, thereby effectively enforcing environmental innovation and leading to a reduction in carbon emissions.Originality/valueThis study integrated governance and environment-oriented variables in the model to empirically examine the role of financial constraints on the carbon emissions of the firms in the USA over and above what has already been documented in the earlier literature.

Implementation of Remedial Feedback and Observable Progression System in GFP English Writing

Despite the fact that teachers and students disagree about feedback methods and its efficacy continues to be a major issue in higher education, it is universally understood that effective feedback improves students' performance. This highlights the necessity for a thorough study and greater justification of any potential discrepancies in practices and behaviour. This study aims to investigate and explore both teachers' and students' acceptance of written corrective feedback and concerted effort towards observable improvement. This study also intends to evaluate related narratives, methods, and constraints that prevent or augment such effectiveness. Furthermore, the outcome of this research will focus on designing and implementing the written corrective feedback as an observable improvement strategy in General Foundation Program (GFP) English writing classrooms. To substantiate the research objectives, an experimental and a control group consisting of 10 teachers each and 100 GFP English students with 25 from level 3 will be subjected for experimental evaluation.

Discrete-continuous model for facility location problem with capacity-cost relation constraints

The facility location problem (FLP) involves optimally locating a set of facilities that must satisfy the demands of a group of customers distributed in a planar area. Traditionally, various FLP models have been applied to find new facilities by considering already-existing facilities, and choosing new locations among a given set of discrete candidates. These are unreasonable because a limited set of candidates may not include the optimal locations. In this study, we developed a mathematical model based on mixed-integer linear programming (MILP) for FLP. In this model, the locations of existing facilities are known and categorized as discrete. On the other hand, the locations of new facilities to be found are categorized as continuous and discrete. In addition, the optimal number of new facilities is determined by a judgment formula. The cost of facilities is also considered, including fixed opening costs and variable capacity-related costs. To make the model closer to reality, the entire area is divided into several zones with varying costs. We developed a greedy multiphase location method for the proposed MILP (MPL-MILP) that efficiently determines the exact locations of new facilities in a stepwise manner. For large-scale problems, we developed a two-variable-based dynamic iterative partial optimization (TVB-DIPO) to obtain near-optimal solutions within a given time limit. Computational experiments were conducted to test the performance of the proposed MPL-MILP and TVB-DIPO. The results indicate that MPL-MILP is suitable for small- and medium-sized problems with exact solutions, while TVB-DIPO is more suitable for large-scale problems with higher solution efficiencies.

Changes in reproductive policies in Hungary between 2010 and 2022

This paper examines Hungarian reproductive policies, their changes and their restrictions in relation to pronatalist objectives between 2010 and 2022. The aim of the study is to present and interpret legislative changes in reproductive policies in the context of the pronatalist policies in Hungary. Reproductive policies include the regulation of assisted reproductive technologies, adoption, abortion, contraception, and sex education. In the development of these policies, we assume that a fundamentally pronatalist approach prevails, but we also identify various specific related constraints: heteronormativity, marriage-centredness, and the maintenance and reinforcement of traditional gender roles. We assume that Hungary’s reproductive policies have become increasingly selective since 2010 after the second Orbán government. These policies can be considered selective because they do not encourage all social groups to have children. These result in the exclusion of for example socially disadvantaged groups, single people and same-sex couples from reproduction due to legal constraints, a lack of financial support, access, and transfer of information. In conclusion, selective, heteronormative and marriage-based pronatalism is most identifiable in the adoption context, but abortion regulation, the legal environment for assisted reproductive technologies and sex education, in general, may reinforce pronatalist objectives.

Impact of local processing of agricultural raw materials on job creation in the West African Monetary and Economic Union

Purpose. This work evaluates the relationship between the processing of agricultural raw materials and the level of employment in the West African Monetary and Economic Union (WAEMU).
 Methodology / approach. The Dynamic Common Correlated Effects (DCCE) estimation proposed by Chudik and Pesaran (2015) is used. The data for this study come from the World Bank and the International Labour Office and cover the Consumer Price Index, human capital, trade openness, foreign direct investment, and agricultural manufacturing industry for the period 1990–2019.
 Results. The results show that agricultural manufacturing, human capital and foreign direct investment have positive influences on job creation in WAEMU countries in the long term, even if this impact remains small. On the other hand, trade openness and inflation lead to a decrease in employment level. Indeed, the specialization in the export of unprocessed agricultural raw materials with low benefit, the massive import of consumer goods and the delay in terms of global competitiveness in most of these countries justify such results. Therefore, in order to boost job creation, it would be expedient to accelerate the process of developing local industries and promote the production of consumer goods. 
 Originality / scientific novelty. Previous studies on local processing of agricultural raw materials have mainly focused on the production process and related constraints. However, very little work has been done on their effects on economic growth and job creation. This study fills this gap. It extends the existing literature on the causal relationship between local processing of agricultural raw materials and job creation. Finally, the Dynamic Common Correlated Effects estimator is used to address this issue.
 Practical value / implications. The information generated will be useful to a number of organizations, including: research centers, universities, governments, governmental and non-governmental organizations, to better guide the development and implementation of policies and strategies for job creation and unemployment reduction. Finally, by knowing the existing relationship between local processing of agricultural raw materials and job creation, as well as the limitations of this raw material processing policy, the study provides the different ways to improve the capacity for job creation and unemployment reduction. Research on this issue is too important to inform policy makers on the structural transformation of their economies to achieve full economic growth and reduce the unemployment problem.

Unveiling the Factors Influencing Organic Tomato (Solanum lycopersicum) Production: An Empirical Evidence from the Mymensingh District of Bangladesh

Tomato is one of the most popular and widely grown vegetables, and faces a demand-supply gap, prompting the need for enhanced production. As global agriculture shifts towards organic practices, this study was undertaken to explore the socioeconomic status of organic tomato producers, assess the factors impacting organic tomato production, and identify the production related constraints. Following the simple random sampling method, a total of 60 organic tomato producers were selected from two villages in Gouripur Upazila under the Mymensingh district and they were interviewed using a structured interview schedule. The research reveals that the majority of farmers were within the productive age range of 36-50 years, with male dominance in the field. Family sizes were diverse, with medium-sized families being the most prevalent. A substantial proportion of farmers possess secondary-level education. Experience in organic tomato farming ranges from 5 to over 15 years, indicating a diverse level of expertise. The Cobb-Douglas revenue type production function was used to determine the effect of selected inputs on organic tomato production. The findings of production function analysis revealed that costs related to human labor, seed, organic fertilizer, bio-pesticides, and land use positively impact organic tomato production. The study also identified major problems faced by farmers in organic tomato production in which high disease and pest attacks were the most significant problems in the study area. Therefore this study will be helpful for farmers to increase organic tomato production and relevant policymakers to support organic tomato producers and further promote sustainable agriculture in this region.

How Does Time Pressure Influence Risk Preferences? Answers from a Meta-Analysis

Abstract Four decades of research into the influences of time pressure on risky decisions have produced widely contrasting findings: 38.5% of the effects indicate that time pressure increases risk preferences, whereas 61.5% show the opposite. A theoretical framework with four conceptual categories of moderators is proposed to explain these heterogeneous findings: nature of the time constraint, negative outcome salience, negative outcome severity, and vulnerability to the outcomes. This framework is tested through a meta-analysis of 213 effect sizes reported in 83 papers, representing 65,574 unique respondents. The four categories of moderators effectively resolve notable conflicts. For example, regarding the nature of the time constraint, an absolute versus relative constraint increases risk preferences, but an ambiguous versus objective constraint decreases risk preferences. In terms of negative outcome salience, risk preferences decrease if the risk is learned about from a description (vs. experience) or the outcome is framed as a loss (vs. gain). Negative outcome severity also exerts an effect, as discrete choices lower risk preferences compared with attitudinal risk. In addition to managerial and public policy implications based on simulations, a comprehensive research agenda that builds on the robust insights of this meta-analysis is offered.

Calculation and Analysis of Motor Thermal Stress With or Without Eccentricity for In-Wheel Electric Vehicle Applications

The requirement of high-power density and the problems of high temperature and uneven air gap caused by environmental constraints make the alternating effect of internal temperature and related constraints between components during the operation of the motor for in-wheel electric vehicle. These effects and constraints will lead to thermal stress and concomitant deformation, and seriously affect the safe operation of in-wheel motors (IWMs) and vehicles. Aiming at the above problems, this paper takes a 15kW IWM as the research object. Based on the analysis of the mutual coupling relationship between the multi-physics field, such as the electromagnetic field, the temperature field, the flow field and the structural field, a thermal stress analysis model of the IWM is established and verified firstly. Then, quantitative calculation of the thermal stress/strain state of the IWM with or without eccentricity is carried out under different working conditions. The analytical results show that the thermal load generated internally leads to the generation of uneven thermal stress and accompanying thermal deformation, and the maximum thermal stress (MTS) and maximum thermal deformation (MTD) do not appear on the same component. Although eccentricity does not affect the position of the MTS and the MTD, it has an important effect on the maximum value of the stress and deformation, especially the eccentricity exceeds 30%. The results also demonstrate that the permanent magnet (PM) is most significantly affected by the eccentricity.

Security-Constrained Unit Commitment Considering Locational Frequency Stability in Low-Inertia Power Grids

With increasing installation of wind and solar generation, conventional synchronous generators in power systems are gradually displaced resulting in a significant reduction in system inertia. Maintaining system frequency and rate-of-change-of-frequency (RoCoF) within acceptable ranges becomes more critical for the stability of a power system. This paper first discusses the impact of inter-area oscillations on the system rate-of-change-of-frequency (RoCoF) security; then, the limitations on locational RoCoF accounting for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$G - 1$</tex-math></inline-formula> contingency stability are derived. To capture highest locational RoCoF during the oscillation, multiple measurement windows are introduced. By enforcing these frequency related constraints, a location based RoCoF constrained security constrained unit commitment (LRC-SCUC) model is proposed. Furthermore, an effective piecewise linearization (PWL) technique is employed to formulate a RoCoF linearization problem and linearize the nonlinear function representing the location based RoCoF constraints in SCUC. Case studies are carried on IEEE 24-bus system to demonstrate the effectiveness of proposed LRC-SCUC model. The results also show that deploying virtual inertia techniques not only reduces the total cost, but also improves the system market efficiency.

Non-contact measurement techniques to study the microsized particle adhesion phenomenon

Airborne microsized particles are generated by artificial activity and natural sources. Due to their characteristics, these airborne particles are highly volatile and can cover thousands of kilometers according to weather conditions (in particular, wind intensity and humidity). As a result, these microsized particles could contaminate engineering systems determining their operation and performance modification. Phenomena such as photovoltaic panel soiling or gas turbine fouling are two of the most detrimental effects generated by the interaction between airborne particles and the relevant surfaces of the system. The present work proposes a set of non-contact measurement methodologies to study the adhesion phenomenon. The non-contact techniques are devoted to studying the deposited layer without altering the deposits. Image and video analysis have been used to show how the deposit can be studied in detail. Stationary and rotating facilities have been employed to show the applicability and the related constraints to the non-contact measurement techniques.

A Dimensionality-Reducible Operational Optimal Control for Wastewater Treatment Process.

Operational optimal control (OOC) is an essential component of wastewater treatment process (WWTP). The control variables usually are high-dimensional, nonlinear, and strongly coupled, which can easily fail traditional optimization control methods. Mathematically, these operational variables usually are in the unknown low-dimensional space embedded in the high-dimensional space. Therefore, the OOC problem of WWTP can be resolved as an optimization challenge involving low-dimensional space, and the unknown low-dimensional space is presented in the form of a set of controlled variables in a high-dimensional space, which is normal in real-world industries. Here, a dimension-reducible data-driven optimization control framework for WWTP is proposed. Considering the difficulty in elucidating the whole space of set points, a neural network is designed to approximate the constraint relationship between control variables. The search process is based on optimization methods in low-dimensional space embedded into Euclidean spaces. Furthermore, the convergence of the process is ensured via mathematical analysis. Finally, the experimental simulation of wastewater treatment revealed that this approach is effective for an optimal solution in control systems.

Graph Database and Matrix-Based Intelligent Generation of the Assembly Sequence of Prefabricated Building Components

The assembly of prefabricated components is a critical process in prefabricated building construction, influencing both progress and accuracy. However, the assembly sequence planning and optimization (ASPO) of prefabricated components have yet to receive sufficient attention from researchers, and current research has displayed limited automation and poor generalization capabilities. Therefore, this paper proposes a framework for intelligently generating assembly sequences for prefabricated components based on graph databases and matrices. The framework utilizes an adjacency matrix and interference matrix-based modeling method to comprehensively describe the connections and constraint relationships between components, enabling better evaluation of assembly difficulty during optimization. The graph database serves as the central hub for data exchange, facilitating component information storage, automatic querying, and summarization. The obtained assembly sequence and progress plan are fed back into the graph database. To accomplish assembly sequence optimization, a genetic algorithm based on the double-elite strategy is employed. Furthermore, the effectiveness of the proposed framework is validated through an actual engineering case. The results demonstrate that the framework can effectively find an optimal assembly sequence to mitigate the assembly challenge of a prefabricated building.

Distributed observer‐based fixed‐time cooperative guidance law against maneuvering target

SummaryThis paper presents a fixed‐time cooperative guidance law for leader‐following missiles, comprising one leader missile with the target seeker and several seeker‐less follower missiles. The aim is to achieve a simultaneous attack on a maneuvering target at desired impact angles. First, a guidance law with impact angle control for the leader missile against a maneuvering target is proposed based on nonsingular fast terminal sliding mode (NFTSM) control algorithm. Then, the design of cooperative guidance law for the follower missiles is composed of two parts: along the follower‐to‐leader line of sight (LOS) direction, the guidance command derived from bi‐homogeneous property is designed to ensure that the follower‐leader ranges keep proportional consensus with the range‐to‐go of the leader missile, thus avoiding the estimation of time‐to‐go (); in the normal follower‐to‐leader LOS direction, considering the relative impact angle constraints which is determined by the leader LOS angle, the guidance command is proposed based on predefined‐time sliding mode control method. What's more, a distributed fixed‐time observer is designed for the follower missiles to compensate for unobtainable leader missile information. The fixed‐time stability of the proposed methods is demonstrated using the Lyapunov theory and bi‐homogeneous property. Finally, simulation results confirm the effectiveness and superiority of the proposed fixed‐time cooperative guidance law with leader‐following strategy.

Perceived Constraints in High-Density Apple Cultivation by the Farmers of the Mid-Hills Area of Himachal Pradesh

The study was carried out in area of Kandaghat and Solan blocks of Himachal Pradesh, India from November 2021 to April 2022 to study the constraints in high-density apple cultivation by the farmers of the mid-hills area of Himachal Pradesh, India. The present study fully relied on the primary data through a properly structured schedule for the production year 2021–2022, with a sample size of 60 farmers involved in high-density apple plantations. Garret’s ranking technique was used to find constraints perceived by the high-density apple cultivators. The objective of the research was to identify the prevailing problems of the high-density apple sector in the selected area. In this study the major problems faced by the high-density apple growers in production were the high cost of high-density apple plants, followed by identifying the disease, costly labor, and lack of technical guidance. Major marketing-related constraints expressed in the marketing of high-density apples were the problem of fluctuation of price, the high price of transportation, distant market, and high commission charges, further the data revealed that the major environmental and other related constraints were that the grading process and certification process seemed to be costly, problems from hailstorms were also found. The study also highlighted the need of proper marketing facilities as marketing helps in improving the living standard and eliminate the constraints in product and services.

How limiting is finance for Dutch dairy farms? A dynamic profit analysis

AbstractAccessibility to financial resources is considered a prevalent problem in the agricultural sector. We develop an approach to quantify the long‐term opportunity costs of financial constraints in relation to peers who do not face any financial constraints. Using data on past financial performance, we assess creditworthiness and the size of an additional accessible bank loan to farmers. Combining this with data on reported expenditure, we determine the accessible finance. We quantify the opportunity cost as the forgone dynamic profit (intertemporal profit in current‐value terms) from financial constraints. Using data envelopment analysis, we apply our approach to 264 specialised Dutch dairy farms for the years 2006–2017 and explore the potential impact of changes in finance provision for several scenarios. Our results show an increasing gap between frontrunners and other farmers, as the latter generate progressively less dynamic profit in comparison to their best peers. The gap between the dynamic profit of the average farm and that of its best peers from their production and investment decisions made over the span of 1 year grew from €40,040 in 2009 to €114,548 in 2017. However, the growth is not driven by insufficient access to finance. Financial constraints can only explain 6% of the forgone dynamic profit in 2009 and as little as 1% for 2017. The number of farms classified as financially constrained in comparison to their peers decreases in our sample from 44% in 2009 to 8% in 2017. This suggests that non‐financial factors are driving the growing gap.