Adjustment Process Research Articles

Design and Characterization of a Traveling-Wave Antenna for Millimeter Applications in the Sub-THz Band

The main challenge in manufacturing antennas in the sub-THz band is their small size, which requires adapted manufacturing tools. This paper proposes a uniform linear 3 × 1 traveling-wave antenna array (ULTWAA) for millimetre applications in the sub-THz band. The designed array allows a continuous beam orientation of ±46.1° in the E-plane. A small quarter-wave line added to the ends of the antenna allows the beam to be oriented towards the inside of the antenna, cancelling out surface waves and adapting the impedance to the scanning angle. Thanks to this device, the waves produced are progressive. The antenna manufactured at 100 GHz measures 13 × 9.7 × 0.125 mm. The measured peak gain is 14.2 dBi with 70% bandwidth. For in-phase radiation, the distances between the antenna units have been adjusted, but the adjustment process is tedious due to the interdependence between the antenna units.

Power System Operation Mode Calculation Based on Improved Deep Reinforcement Learning

Power system operation mode calculation (OMC) is the basis for unit commitment, scheduling arrangement, and stability analyses. In dispatch centers at all levels, OMC is usually realized by manually adjusting the parameters of power system components. In a new-type power system scenario, a large number of new energy sources lead to a significant increase in the complexity and uncertainty of a system structure, thus further increasing the workload and difficulty of manual adjustment. Therefore, improving efficiency and quality is of particular importance for power system OMC. This paper first considers generator power adjustment and line switching, and it then models the power flow adjustment process in OMC as a Markov decision process. Afterward, an improved deep Q-network (improved DQN) method is proposed for OMC. A state space, action space, and reward function that conform to the rules of the power system are designed. In addition, the action mapping strategy for generator power adjustment is improved to reduce the number of action adjustments and to speed up the network training process. Finally, 14 load levels under normal and N-1 fault conditions are designed. The experimental results on an IEEE-118 bus system show that the proposed method can effectively generate the operation mode under a given load level, and that it has good robustness.

Health Insurance Claims Management Issues in Georgia

In the insurance market, the study of the adjustment of the amount requested by the medical organization is vital to ensure the stability of the industry and customer satisfaction. The research aims to analyze the adjustment process in the insurance market and to study the factors affecting the effective management of losses. According to research, the cost of the work performed by the medical institution is adjusted according to three main criteria: reimbursement, deadlines and discount. During adjustment, the following problems are identified: failure to consider the terms of the contract, neglect of its clauses, provision of disorderly documentation, and demand for compensation in an unscrupulous manner. The largest share of adjustments comes from hospitals, followed by pharmaceutical companies, outpatient clinics, and finally dental clinics. Although human health is important for medical organizations and insurance companies, their main goal is to increase revenues and make the right distribution for future purposes. It is important that insurance companies and medical institutions integrate software to eliminate problems, which will reduce deadlines, the risk of providing unnecessary services and other factors that cause adjustments.

High-resolution-gridded rainfall dataset derived from surface observation by adjustment of satellite rainfall product

A high-resolution-gridded rainfall dataset is essential for many purposes. Such as analysis of extreme weather conditions, natural-disaster mitigation, or to be used as an input to the hydrological model. Satellite-based rainfall products (e.g., Global Satellite Mapping of Precipitation-GSMaP) can solve the spatial and temporal issues despite their rainfall intensity often being under or overestimated. This research aims to provide a high-resolution rainfall dataset by adjusting the 0.1 deg GSMaP rainfall data to the surface rainfall data from several observation points in the greater Jakarta area (Jabodetabek) during January 2020 when several flooding occurred in Jakarta. The adjustment process includes calculating the bias between the satellite estimation in the nearest observation point and interpolating the error back to the 0.01 deg grid by using radial basis function (RBF) to obtain the correction factor in every grid point, GSMaP data then adjusted by the correction factor. We implemented the method in January 2020 when several floods occurred in Jakarta. The result reveals a more realistic rainfall spatial distribution than regularly interpolating the observation data. The validation of adjusted rainfall estimation at the verification points also shows a reduction in domain-wide RMSE by 30 – 80%.

Displacement Values Calculation Method for Ship Multi-Support Shafting Based on Transfer Learning

Deviations between the design and actual shafting occur due to limitations in ship construction accuracy. Consequently, accurately obtaining the relationship between the actual shafting load and displacement relationship based on the design shafting becomes challenging, leading to inaccurate solutions for bearing displacement values and low alignment efficiency. In this research article, to address the issue of incomplete actual shafting data, a transfer learning-based method is proposed for accurate calculation of bearing displacement values. By combining simulated data from the design shafting with measured data generated during the adjustment process of the actual shafting, higher accuracy can be achieved in calculating bearing displacement values. This research utilizes a certain shafting as an example to carry out the application of the bearing displacement value calculation method. The results show that even under the action of shafting deviation, the actual shafting load and displacement relationship model can become more and more accurate with the shafting adjustment process, and the accuracy of bearing displacement values calculation becomes higher and higher. This method contributes to obtaining precise shafting adjustment schemes, thereby enhancing alignment quality and efficiency of ship shafting.

Importance-aware data selection and resource allocation for hierarchical federated edge learning

Compared to traditional machine learning approaches, federated learning (FL) is effective in dealing with mobile device data privacy issues. Apart from utilizing the cloud computing server as the model aggregation center, edge computing servers can also be advocated as intermediaries to perform model aggregation near the devices, which can reduce transmission latency and energy consumption. In this paper, we consider a multi-layer federated edge learning framework where both cloud and edge servers are used for FL and design a Data Importance-aware Hierarchical Federated Edge Learning (DHFL) scheme. We develop a joint data selection and resource allocation algorithm based on data importance to maximize learning efficiency in DHFL. To solve this problem, we decompose it into three sub-problems including edge-device association, resource allocation and data selection. By presenting the optimal strategy for each edge-device group, the optimal association between devices and edge servers is achieved through an iterative global cost reduction adjustment process, and data selection is performed by using convex optimization scheme. Extensive simulations are carried out to verify the proposed scheme and show that our proposal can achieve smaller training loss using less than 1/6 of the data and reduce latency by 80% compared to FedAvg.

Contemporaneous causality among office property prices of major Chinese cities with vector error correction modeling and directed acyclic graphs

PurposeThis study aims to investigate dynamic relations among office property price indices of 10 major cities in China for the years 2005–2021.Design/methodology/approachUsing monthly data, the authors adopt vector error correction modeling and the directed acyclic graph for the characterization of contemporaneous causality among the 10 indices.FindingsThe PC algorithm identifies the causal pattern, and the linear non-Gaussian acyclic model algorithm further determines the causal path from which we perform innovation accounting analysis. Sophisticated price dynamics are found in price adjustment processes following price shocks, which are generally dominated by the top tier of cities.Originality/valueThis suggests that policies on office property prices, in the long run, might need to be planned with particular attention paid to the top tier of cities.

Adaptive adjustment after conflict with group opinion: evidence from neural electrophysiology.

Individuals inherently seek social consensus when making decisions or judgments. Previous studies have consistently indicated that dissenting group opinions are perceived as social conflict that demands attitude adjustment. However, the neurocognitive processes of attitude adjustment are unclear. In this electrophysiological study, participants were recruited to perform a face attractiveness judgment task. After forming their own judgment of a face, participants were informed of a purported group judgment (either consistent or inconsistent with their judgment), and then, critically, the same face was presented again. The neural responses to the second presented faces were measured. The second presented faces evoked a larger late positive potential after conflict with group opinions than those that did not conflict, suggesting that more motivated attention was allocated to stimulus. Moreover, faces elicited greater midfrontal theta (4-7Hz) power after conflict with group opinions than after consistency with group opinions, suggesting that cognitive control was initiated to support attitude adjustment. Furthermore, the mixed-effects model revealed that single-trial theta power predicted behavioral change in the Conflict condition, but not in the No-Conflict condition. These findings provide novel insights into the neurocognitive processes underlying attitude adjustment, which is crucial to behavioral change during conformity.

Effect of Various Acid Solutions on the CO2 Dissolution Rate, Morphology, and Particle Size of Precipitated Calcium Carbonate Synthesized Using Seashells.

In this study, the influence of acid solutions on the production of precipitated calcium carbonate (PCC) using seashells was investigated. In terms of the Ca dissolution efficiency and atmosphere for dissolving CO32-, the results indicate that HCl, HNO3, CH3COOH, and HCOOH at 1.0 M were the most ideal among the acid solutions. The use of weak acids resulted in the low degree of dissolution of Al and Fe. These impurities could be mostly removed through the pH adjustment process, leading to PCC with a purity of 99% or more. Further, CH3COOH and HCOOH exhibited low CaCO3 carbonation efficiency owing to the hydrogen bonding of the carboxyl group and its hindering effect on the growth of CaCO3 particles. In addition, in the presence of the carboxyl group, the morphology tended to be oval, and the particle size was small. Particularly, when CH3COOH was used, the combined effect of the low initial Ca ion concentration and slow CO2 dissolution rate resulted in minimal changes during the carbonation time and the smallest particle size. However, variations in the degree of Ca concentration with a change in the acid solution concentration influenced the dominance of nucleation and particle growth, leading to variations in the particle size. The results of this study revealed that when manufacturing PCC using seashells, the appropriate acid solution must be selected to obtain the required PCC properties.

On the Vertical Structure of Mesoscale Eddies in the Kuroshio‐Oyashio Extension

AbstractVertical structure of mesoscale eddies is key to the eddy‐induced heat/material transport that further affects the climate and marine ecosystem. This study explores the vertical structure of mesoscale eddies in the Kuroshio‐Oyashio Extension region (KOE) and its underlying dynamics. By applying the hierarchical ascending classification to the observational and reanalysis data sets, we classify mesoscale eddies with three distinct kinds of vertical structures. Each kind of eddies exhibits clear spatial aggregation along a distinct zonal band. Eddies have core depths of 100–300 m in the northern part of the KOE and core depths of 300–500 m and 0–100 m in the southern. The eddy splitting or merging does not introduce new kind of eddy vertical structure but causes large intra‐kind variability. The different kinds of eddy vertical structures can be partially accounted for by the baroclinic instabilities at the eddy generation sites and local adjustment process.

HYBRID ADJUSTMENT OF UAS-BASED LiDAR AND IMAGE DATA

Abstract. Several advancements are going with Unmanned Aerial Systems (UAS) with the addition of multiple sensors and simultaneous data acquisition to obtain detailed geo-data for various applications. However, simultaneous data acquisition with multiple sensors, namely camera, and LiDAR, will also result in possible discrepancies associated with them, and they need to be solved to use a reliable and accurate final product. Several errors can be associated with both camera and LiDAR datasets due to the different characteristics of the sensors and terrain conditions. This research paper aimed to minimize the errors between LiDAR and the image datasets simultaneously acquired with an Unmanned Aerial System (UAS) by implementing a hybrid adjustment approach with a criterion for the roughness and threshold angle between surface normals. The initial trajectory of the UAS, raw LiDAR measurements, and image observations were the inputs used for the hybrid adjustment. The hybrid adjustment workflow minimizes the discrepancies with a least-squares-based simultaneous adjustment for both LiDAR and image datasets. For the hybrid adjustment process, three types of correspondences were established, namely: between image pairs, overlapping LiDAR strips, and between Image tie points and LiDAR strips. For quality control, mean Cloud-to-Cloud distances (C2C) were compared between both LiDAR and camera point clouds before and after hybrid adjustment. The surface-level analysis of the results was also carried out to analyze the errors before and after hybrid adjustment at a surface level for different types of surfaces. The results showed that the alignment between the point clouds has significantly improved from the range of meters to a centimeter-level after implementing the hybrid adjustment process. The proposed hybrid adjustment workflow can be used in mapping applications where a centimeter-level accuracy is requested.

Posture planning method for complex feature measurement using a single-line laser scanner

A single-line laser scanner is commonly utilized for measuring complex surfaces and contours. However, achieving automatic implementation of this scanner poses challenges in terms of designing a measurement posture that considers measurement accuracy, path planning, and the positioning of auxiliary equipment. This ensures non-interference during the measurement process. In this study, we focus on the application of T-SCAN. First, we construct a measurement posture parameter model for T-SCAN and analyze the viewpoint position’s coverage of the measurement area. Second, we propose a measurement path planning method based on scanning posture to minimize overlapping areas. Lastly, we present a measurement station planning method based on scanning postures and analyze the transfer error of the measurement targets to establish a unified measurement field. Experimental results demonstrate that, after the posture adjustment process, the average distance deviation between the measurement data and the theoretical model is significantly reduced.

Brandeis in Brussels? Bureaucratic discretion, social learning, and the development of regulated competition in the European Union

AbstractNeo‐Brandeisian legal scholars have recently revived the ideas of Supreme Court Justice Louis Brandeis, who championed state regulation that preserved market competition and economic liberty in the face of concentrated private power. Yet ultimately and perhaps paradoxically, it has been Europe and not the United States that has proved more hospitable to accommodating key features of the Brandeisian approach. We explain this outcome by tracing the evolution of EU competition law to gain insight into the social learning processes through which such regimes change over time. We argue that the EU's administrative system, which provides the European Commission with significant bureaucratic discretion, has facilitated processes of ongoing deliberative adjustment to policy and practice, which over time has resulted in a system of “regulated competition” with striking similarities to the Brandeisian vision. The analysis highlights how administrative law institutions condition how regulatory regimes evolve in response to acquired experience and knowledge.

Mathematical model of the hovercraft lift system

BACKGROUND: Currently, hovercrafts are used worldwide thanks to their amphibian capabilities and mobility at water and slightly prepared areas with low supporting properties. Whereas, in practice, hovercrafts have two main systems ensuring motion, lift and traction which can be combined (operating from a common source of mechanical energy) as well as separated.
 This paper considers a hovercraft with separated lift and traction systems. The lift system of this hovercraft consist of piston diesel internal combustion engine (ICE), hydrostatic transmission, axial fans, feeding channel and an air-cushion plenum. The considered variant is chosen because hydrostatic transmission has a number of sufficient advantages in comparison with mechanical transmission with universal shafts and pulley drives, widely used at present time. The paper considers the open plenum lift system.
 AIM: Development of the combined mathematical model of the hovercraft lift system consisting of piston diesel ICE, hydrostatic transmission and a fan supplying air into the air-cushion plenum.
 METHODS: Using the MATLAB/Simulink environment, the engine power adjustment at hovercraft motion on various ground surfaces is studied with regard to increasing the efficiency of the fan and the whole system. Analytical scheme of the system is given, acceptable transient characteristics are obtained. Efficiency and range of optimal operation of the Sauer-Danfoss pump and hydraulic motor are estimated. The process of hovercraft adjustment from the established mode to a new state when motion condition change is considered.
 RESULTS: According to the simulation results, there is influence of the income control signal (adjustment parameter of engine operation modes) and disturbance signal (pressure change coefficient that defines properties of ground surface) on parameters describing the hovercraft motion.
 CONCLUSION: The developed mathematical model helps to choose and evaluate adjustment parameters of engine operation modes at hovercraft motion on various ground surfaces, to analyze and to improve the system energy efficiency.

A Soufflé only Rises Once: China’s Grim Economic Prospects

Abstract After four decades of unprecedented growth, the Chinese economy faces a plethora of structural problems: The bursting of the world’s largest real estate bubble, the demographic decline and the turn to a preference for autarky are resulting in a potent mix. Solving the above-named problems will results in a prolonged phase of slow growth or even stagnation. Not tackling the issues will be even worse, for the adjustment process will eventually be even more painful. Real estate is probably the biggest issue. Too many apartments were built for too few people. The second key problem is the demography. The United Nations are suggesting that China’s population may shrink to about half its current level by 2100. Since China does not consider immigration, the aging population will be a drag on economic development and, of course, real estate. The Chinese Communist Party has engineered an economic mirage: That soufflé will only rise once.

Pretreatment of 3-hydroxyacetophenone in pharmaceutical wastewater using combined salting-out crystallization+ Fenton system and subsequent impact analysis of effluent water

ABSTRACTSelecting a suitable pretreatment process for pharmaceutical wastewater that is difficult to treat biochemically so that it can enter the subsequent biochemical treatment. In this study, pharmaceutical wastewater consisting of 45 g/L sodium bisulfate, 9 g/L 3-hydroxyacetophenone (3-HAP), and 36.75 g/L sulfuric acids,which is a kind of typical pharmaceutical wastewater, was used for the pretreatment case study, and the process was screened by technology. A salting-out crystallization+Fenton system(SC-F) was developed for the treatment of this wastewater. The salting-out agent is formed by the pH adjustment process without additional additions and the salting-out crystallization effect is significant for the precipitation of 3-HAP from the wastewater. Subsequently, the optimal operating conditions for SC-F were derived from experiments as H2O2 of 0.4692 mol/L, n(H2O2):n(Fe2+)=30:1, pH=3. Under optimal conditions, the reaction time of 2 h achieved a COD removal rate of 90% and a BOD/COD value of 0.56, confirming the effectiveness of the technology in treating this wastewater. Additionally, it was discovered that the Fenton treatment was not significantly impacted by the inorganic components of the effluent. Analysis of effluent properties and possible effects on subsequent treatment by LC-MS and toxicity analysis. The results show that the biodegradability are enhanced by the pretreatment technology. However, the effluent still suffers from high acidity and high salt content, and this study proposes a solution to this problem. Furthermore, research on the treatment of 3-HAP wastewater has not been reported and this study provides a new case study in the field of wastewater treatment.

Patterns and processes of channel and floodout adjustment in a discontinuous dryland river, semi-arid eastern Australia

Alluvial rivers in semi-arid and arid landscapes are prone to episodic geomorphic adjustments related to long-term sediment accumulation and occasional reworking by flash floods. However, few studies document the rates, patterns and processes leading to channel breakdown, particularly avulsion and floodout. These intrinsically driven adjustments may pose a risk to water resource availability through redistribution of water and sediment on the floodplain. To address this knowledge gap, channel change associated with avulsion and flooding in the last ∼30 years were quantified for Little Faulkenhagen Creek, a dryland river of the Murray-Darling Basin, Australia. The semi-arid, low gradient catchment promotes transmission losses, which with loss of valley confinement leads to channel adjustment and contraction to occur where water, sediment and energy are spread across the floodplain. Pronounced downstream changes occur in channel capacity (i.e., reductions in bankfull width, depth and area) and hydrology (i.e., reductions in bankfull discharge and stream power) as the river enters the floodout zone. Vegetation roughness increases in and around the floodout, where shrubs and river redgum trees line and encroach upon the channel. Mapping and analysis of hydro-geomorphological parameters using cross sections from 1991 to 2021 reveal recent changes in channel capacity, discharge and stream power. The upper reach has experienced substantial channel widening from erosion, while the lower reach leading into the floodout has contracted because of sediment deposition within the channel. Unchannelised floodwaters are deflected around a raised alluvial ridge and over the floodout eventually dropping into several migrating upstream knickpoints (head-cutting gullies) with retreat rates up to 32 m a−1. Therefore, both the existing channel slope (i.e., decline) and potential avulsion courses (i.e., increase) are affected by reduced energy and enhanced sedimentation. The net result of upstream in-channel sedimentation and aggradation on the floodout and downstream incision and gullying is that the floodout has migrated ∼1 km upstream and the river is at risk of a secondary avulsion as gullies retreat towards the main channel, potentially circumventing the floodout within ∼11 years. An erosion cell conceptual model is suitable for this system, where sediment from the local upstream production (erosion) zone is transferred downstream to a sink (deposition) zone. Erosion and deposition will fluctuate over the long-term, leading to periods with dominantly incisional or aggradational processes. Cycles of erosion and deposition will vary over time and external forces may influence a wholesale shift to a new fluvial state. Understanding the context and patterns of recent dryland river adjustments, as well as the dominant processes and their variability, can assist water and land management.

Fractional calculus applied to the Cournot-type adjustment model

In this contribution, we propose the incorporation of memory in a Cournot-type model for the process of adjusting the production of firms in a duopoly market, through the calculation of fractional order. Under the simplifying assumption that the inverse demand and costs of firms are affine functions of the quantities produced, we show numerically some conditions on memory (fractional derivative order) and on the speed of the adjustment process, so that the model proposed converges to Cournot's generalized stationary points. Under these assumptions, we show that the firm that has more memory obtains greater profit.

Exploring the evolutionary mechanism of the cross-regional cooperation of construction waste recycling enterprises: A perspective of complex network evolutionary game

Cooperation and information sharing among various regional departments play a crucial role in facilitating the equitable disposal of construction waste across regions, fostering regional coordination in waste management. This paper establishes the complex network evolutionary game model of cross-regional cooperation of construction waste recycling enterprises, and conducts numerical simulation to analyze the strategic adjustment process of recycling enterprises under the coordination and complementarity of market mechanism and government mechanism, and explores the Pareto optimal conditions that are conducive to cross-regional cooperation of recycling enterprises. The result indicates that with the increase of the market scale of cross-regional treatment of construction waste, it can effectively improve the willingness of cross-regional cooperation of recycling enterprises. In the market mechanism, both the profit distribution and synergistic benefit have a significant impact on the cross-regional cooperation behavior of construction waste recycling enterprises, while the impact of spillover benefit is relatively minor in comparison. In various network scales, the profit distribution coefficients exhibit threshold values within the ranges of 0.3–0.35, 0.25 to 0.3, and 0.25 to 0.3, respectively. Within the government mechanism, the government subsidy coefficient falls within the threshold of 0.3–0.4. Notably, greater government support proves more conducive to advancing cross-regional cooperation among recycling enterprises. For small-scale and medium-scale markets, there exists a threshold for default penalties ranging between 4 and 5. In contrast, large-scale markets have a default penalty threshold between 3 and 4. Imposing reasonable penalties for contract breaches can effectively stimulate the sustainable and consistent development of cross-regional cooperation among recycling enterprises. These findings establish a foundation for shaping cross-regional cooperation strategies for recycling enterprises, enhancing the efficiency of construction waste treatment, and fostering the coordinated development of urban areas.

Modeling the matching stage of HDPE hot plate welding: A study using regression and support vector machine models

AbstractThis research studies the material displacement of high‐density polyethylene (HDPE) during the initial stage of the hot plate welding (HPW) process, called the Matching stage. Newly developed mathematical models simulate the relationship between the main process parameters (force, temperature, and time) and the size of the surface area. The collected data was used to develop four mathematical models for material displacement and time. Two models are machine learning based models (support vector machines). The other two models are regression models in the form of functions. In addition, this study provides a visual representation of HDPE melt displacement with the changes in temperature and pressure. The obtained results indicate that these models can be used for developing a parameter adjustment process or determining specifications for new production equipment. The potential applications of the developed models can be extended to industries that use HPW of HDPE, such as automotive or aerospace. This could result in significant savings in the amount of scrap and waste due to inaccurate and ad hoc settings that currently take place in the industry.Highlights Study of HDPE material displacement in the hot plate welding Matching stage. Visualization of HDPE melt displacement with temperature and pressure changes. Development of SVM and mathematical regression models. Applications in parameter adjustment and equipment specification. Savings in scrap and waste by reducing inaccurate settings.