Processing Path Research Articles

The Inclusion of Power Gyrator Topologies as Energy Processing Cells in Photovoltaic Solar Conversion

This paper will provide a classification of high efficiency switching power-gyrator structures and their use as cells for energy processing in photovoltaic solar facilities. Having into account the properties of these topologies presented in the article, their inclusion in solar facilities allows increasing the performance of the whole installation. Therefore, the design, simulation and implementation of a Gtype power gyrator are carried out throughout the text. In addition, in order to obtain the maximum power from the photovoltaic solar panel, a maximum power point tracking (MPPT) is mandatory in the energy processing path. Therefore, the practical implementation carried out includes a control loop of the power gyrator in order to track the aforementioned maximum power point of the photovoltaic solar panel.

Process Path for Reducing Carbon Emissions from Steel Industry—Combined Electrification and Hydrogen Reduction

This review focuses on the energy structure of iron and steel production and a feasible development path for carbon reduction. The process path and feasible development direction of carbon emission reduction in the iron and steel industry have been analyzed from the perspective of the carbon–electricity–hydrogen ternary relationship. Frontier technologies such as “hydrogen replacing carbon” are being developed worldwide. Combining the high efficiency of microwave electric-thermal conversion with the high efficiency and pollution-free advantages of hydrogen-reducing agents may drive future developments. In this review, a process path for “microwave + hydrogen” synergistic metallurgy is proposed. The reduction of magnetite powder by H2 (CO) in a microwave field versus in a conventional field is compared. The driving effect of the microwave field is found to be significant, and the synergistic reduction effect of microwaves with H2 is far greater than that of CO.

The impact of work values on the professional development of primary and secondary school teachers: A moderated mediation model.

This study explored the relationship between work values and primary and secondary school teachers' professional development, as well as the mediating role of work engagement and the moderating role of perceived organizational support. Eight hundred and seventy-three primary and secondary school teachers were recruited at random to complete work values scale, work engagement scale, perceived organizational support scale, and professional development of primary and secondary schools teachers scale. The results revealed that work values positively predicted professional development; work engagement partially mediated the relationship between work values and professional development, and with the mediating effect accounted for 54.62% of the total effect; perceived organizational support regulated the direct path and the first half path of this mediation process. This study empirically clarified why (through work engagement) and when (perceived organizational support) work values were positively related to professional development among primary and secondary school teachers' in China, contributing to the existing work values and teachers' professional development literature. Future research could be encouraged to extend the findings by integrating theory of internal motivation with organizational support theory toward deepening current understanding of how and when work values can contribute to a teacher's professional development.

Research on the Operation Process, Dilemma and Optimization Path of the Work Class

Research on the Operation Process, Dilemma and Optimization Path of the Work Class

Pay practices and safety organizing: Evidence from hospital nursing units.

Our understanding of how highly reliable care delivery is brought about remains elusive, in part, because there is limited evidence regarding the organizational practices that enable safety organizing-the behaviors and processes underlying high reliability. Because safety organizing relies on discretionary effort and lowering barriers to sharing expertise and discussing threats to safety and errors, we investigate three pay practices and their effects on information sharing and, in turn, safety organizing. Specifically, we examine average pay level, minimum pay rates, and pay dispersion on nursing units and their relationship with information sharing and safety organizing. Cross-sectional analyses of survey data from 1,461 registered nurses in 45 nursing units in three Midwestern hospitals on safety organizing linked to administrative data on pay practices from the organization's human resource systems. Pay data and survey responses were aggregated to the nursing unit level. PROCESS and structural equation modeling were used to simultaneously test for direct and indirect effects of pay variables on information sharing and safety organizing. PROCESS and Mplus path analysis indicated that paying a higher minimum rate in the unit and having lower pay dispersion have indirect, desirable associations with safety organizing through information sharing. Pay practices can help organizations enhance safety organizing. In particular, higher pay rates for the lowest level nurses and lower pay dispersion among nurses are associated with unit-level information sharing and safety organizing. Having pay practices associated with lower within-unit variation and higher pay for the lowest paid members of a unit may be viable strategies for greater information sharing and safety organizing.

ДИАЛОГ КАК НАУЧНАЯ ИДЕЯ: БЕСЕДЫ Д. С. ДМИТРИЕНКО С М. И. ИМХАНИЦКИМ

Dialogues as a form of communication are no less in demand today. To a certain extent, they replenish the knowledge that was previously discovered through epistolary and diary entries. We can talk about “hidden” dialogue, “internal” dialogue, and, of course, dialogue as a form of answering questions during an interview, a conversation with a famous person. Dialogues are attributes of modern knowledge about writers, artists, performing musicians, and conductors. The range of published dialogue books is vast, and their fund continues to be actively replenished. There are various approaches to this format of books: conversations, implied dialogues, interviews. The focus of dialogues on art is clear: to hear the voice of an artist, a writer, a musician answering questions about the creative process, specific works, and life path. At the same time, it is not so common to find books of conversations with scientists, since their works speak for themselves. The more interesting is the recently published book by Imkhanitsky M. I. Dialogues with D. S. Dmitrienko [2015]. Honoured Artist of the Russian Federation, Doctor of Art Criticism, Professor, M. I. Imkhanitsky, whose works have long become scientific classics on a wide range of topics “folk musical instruments”, answers the questions of the famous musician, Honoured Artist of the Russian Federation, Chief Conductor and Artistic Director of the State Russian Folk Ensemble Russia named after L. G. Zykina, D. S. Dmitrienko.

Learning Robotic Milling Strategies Based on Passive Variable Operational Space Interaction Control

This paper addresses the problem of robotic cutting during disassembly of products for materials separation and recycling. Waste handling applications differ from milling in manufacturing processes, as they engender considerable variety and uncertainty in the parameters (e.g. hardness) of materials which the robot must cut. To address this challenge, we propose a learning-based approach incorporating elements of interaction control, in which the robot can adapt key parameters, such as feed rate, depth of cut, and mechanical compliance during task execution. We show how a mathematical model of cutting mechanics, embedded in a simulation environment, can be used to rapidly train the system without needing large amounts of data from physical cutting trials. The simulation approach was validated on a real robot setup based on four case study materials with varying structural and mechanical properties. We demonstrate the proposed method minimises process force and path deviations to a level similar to offline optimal planning methods, while the average time to complete a cutting task is within 25% of the optimum, at the expense of reduced volume of material removed per pass. A key advantage of our approach over similar works is that no prior knowledge about the material is required. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This work is motivated by challenges in emerging fields such as recycling of electric vehicles, where products such as batteries adopt a range of designs with varying physical geometry and materials. More generally, this applies when considering robotic disassembly of any unknown component where semi-destructive operations such as cutting are required. Product-to-product variation introduces challenges when planning cutting processes required to disassemble a component, as contemporary planning approaches typically require advance knowledge of the material properties, shape and desired path to select tool speed, feed and depth of cut. In this paper, we show a mathematical model of milling force embedded in a simulation environment can be used as a relatively inexpensive approach to simulate a broad spectrum of cutting processes the robot may encounter. This allows the robot to learn from experience a strategy that can select these key parameters of a milling task online without user assistance. We develop a framework for controlling a robot using this strategy that allows the stiffness of the robot arm to be modulated over time to best satisfy metrics of productivity (e.g. required cutting time), while maintaining safe interaction of the robot with its environment (e.g. by avoiding force limits), similarly to how a human operator can vary muscular tension to accomplish different tasks. We posit that the proposed method can substitute a trial-and-error strategy of selecting process parameters for disassembly of novel products, or integrated with existing planning approaches to adjust the parameters of milling tasks online.

Superstructure optimization for management of low-density polyethylene plastic waste

The TOC presents the decision-making performed in the superstructure for determining the optimal processing path of waste LDPE. The selection is based on two objectives, the emissions and the economics that are represented in the two axes.

Analysis of the Optimization of the Implementation Process Path of Wage Audit in Accounting Firms

Analysis of the Optimization of the Implementation Process Path of Wage Audit in Accounting Firms

Navigating success: Unveiling the concept framework of “success-route” and its impact on achieving goals in career

This paper presents a new conceptual framework known as the “success-route,” explaining its crucial function in attaining success. The authors examine the core elements of this framework, offering insights into goal definition, the “success-route” to achievement, potential distractions, and critical personality qualities that support achieving goals. To improve understanding, a thorough description of the process path is provided, covering everything from inspiration to achievement. The essential significance of the “success-route” in traversing this relationship is highlighted, emphasizing the fundamental link between motivation and effective goal setting. This approach not only improves comprehension of the relationship between motivation and achievement but also increases success rates by bringing individual passions into line. This meticulously crafted “success-route” serves as a guide, imparting valuable lessons on overcoming inadequacies and empowering individuals on their journey toward success.

Research on effective communication forms and characteristics of public service advertisements for nurturing parenting skills in China

This study is part of a larger research aimed at enhancing effective communication of parenting skills knowledge to Chinese parents. The purpose is to explore how to transform public service advertisements into effective training methods for Chinese parents by studying the media form, content expression, symbolic elements and other aspects of public service advertisements in China. This study documents the identification of effective communication characteristics of PSAs, in which advertisements in the form of cold and hot media have different sensory experience characteristics, their expressions of the central processing path, and the expression of the peripheral processing path of advertisements, which could be transformed to improve information transmission and are attractive to observers. The results found different characteristics in terms of language and nonverbal advertising content, which could create different effects on observers. This article mainly studies the different roles of different media forms, content expression, and symbolic elements in public service advertisements, as well as the communication effects of different forms of public service advertisements under different themes. The results have significant implications for developing a theoretical framework for the efficient dissemination of public service commercials and, consequently, for promoting happier families for developing children by improving parents' parenting knowledge.

OPTIMAL MODEL FOR EVALUATING THE TOTAL DURATION OF A BUSINESS PROCESS

When assessing the performance of business processes, it should be noted that one of the most important operational indicators and evaluation criteria of any company should be the indicator of the duration of the process completion cycle. Cycle duration is the amount of time that passes from the start of a task to the moment it is completed. Time is a critical metric for completing any task as it relates to customer satisfaction and the cost of completing that service. Based on this, the main goal of this work is to find the critical path of a business process and build a mathematical model to determine the objective function. To achieve the set goals, the problem of finding the maximum path in a directed graph constructed according to the list of works of the information system implementation project is considered. In accordance with the list of works, the relationships between them were determined, a network schedule for project planning was constructed, and the main relationships and patterns were identified. Studies of the constructed mathematical model were carried out using the MS Excel software application. The critical path of the business process of implementing an information system was found and conclusions were drawn on the total duration of the project. Thus, operations lying on the critical path require additional slack planning.

Causative constructions in process: How do they come into existence in learner writing?

Abstract This article examines the processes through which English causative constructions with MAKE are produced by French-speaking learners. It relies on data from the Process Corpus of English in Education (PROCEED), in which every text is accompanied by a keylog file and a screencast video. These data make it possible to observe the process paths of constructions as they unfold, from their appearance in the text to their evolution (and possible disappearance) through revision. The analysis shows that almost 20% of the causative constructions do not make it to the final version of the text, either because the idea of causation disappears altogether or because it is expressed in a different way. Among the causative constructions that are kept in the finished text, most still undergo some changes, which range from the simple correction of a typo to the transformation of the complement type (e.g. a verbal complement becoming an adjectival complement). Some of these changes are the result of dictionary consultation, also visible in the process data. In addition, the keylog files reveal the presence of pauses during writing, whose investigation can improve our understanding of the mental processing of causative constructions. It thus turns out that in almost 40% of the cases, the causative constructions are immediately preceded and followed by a pause, which could indicate that they are stored holistically in learners’ minds. Besides providing insights into the processes through which causative constructions come into existence in learner writing, this study also illustrates how writing process data can bring us closer to what the reality of writing looks like for language learners.

Protein–protein interaction site prediction by model ensembling with hybrid feature and self-attention

BackgroundProtein–protein interactions (PPIs) are crucial in various biological functions and cellular processes. Thus, many computational approaches have been proposed to predict PPI sites. Although significant progress has been made, these methods still have limitations in encoding the characteristics of each amino acid in sequences. Many feature extraction methods rely on the sliding window technique, which simply merges all the features of residues into a vector. The importance of some key residues may be weakened in the feature vector, leading to poor performance.ResultsWe propose a novel sequence-based method for PPI sites prediction. The new network model, PPINet, contains multiple feature processing paths. For a residue, the PPINet extracts the features of the targeted residue and its context separately. These two types of features are processed by two paths in the network and combined to form a protein representation, where the two types of features are of relatively equal importance. The model ensembling technique is applied to make use of more features. The base models are trained with different features and then ensembled via stacking. In addition, a data balancing strategy is presented, by which our model can get significant improvement on highly unbalanced data.ConclusionThe proposed method is evaluated on a fused dataset constructed from Dset186, Dset_72, and PDBset_164, as well as the public Dset_448 dataset. Compared with current state-of-the-art methods, the performance of our method is better than the others. In the most important metrics, such as AUPRC and recall, it surpasses the second-best programmer on the latter dataset by 6.9% and 4.7%, respectively. We also demonstrated that the improvement is essentially due to using the ensemble model, especially, the hybrid feature. We share our code for reproducibility and future research at https://github.com/CandiceCong/StackingPPINet.

Application of friction surfacing for solid state additive manufacturing of cylindrical shell structures

Solid-state additive manufacturing (AM) via friction stir based processes is gaining increased attention as these techniques are feasible for several similar and dissimilar material combinations and induce significantly lower energy input to the subjacent structure than fusion-based approaches as material melting is avoided. Available research concentrates on linear depositions; however, further development of these techniques towards application necessitates more complex deposition paths, e.g. curves and the crossing of edges of previously deposited layers. In this study, the solid-state layer deposition process of friction surfacing (FS) is investigated in terms of process behavior and appearance of the resulting deposit when curved deposition paths are applied. With advancing side on the curve's inner edge, material build-up occurs predominantly on this side of the layer, which results in a deposit of inhomogeneous thickness. This phenomenon is related to the FS process characteristic due to the superposition of rotational and travel movement on a curvature, and is more pronounced for curves with small radii. A further challenge exists for closed structures, where the deposition has to cross previously deposited layers. This can be successfully achieved by reducing the travel speed prior to passing the edge to provide sufficient plasticized material thickness below the stud tip. Overall, the study provides an understanding of the FS process behavior and process parameters for curved paths. Furthermore, recommendations for process control and path planning, e.g. for building closed cylindrical shell structures, are deduced.

Target-path planning and manufacturability check for robotic CLT machining operations from BIM information

Mass timber is one of the trending construction styles in the last years thanks to its sustainability and offsite manufacturing properties, where cross laminated timber (CLT) is the most common material used. In an effort to link design and manufacturing information in a single location, this study proposes a generative process planning algorithm for CLT machining in robotic environments. The algorithm focuses on automatic feature-based interpretation of the geometry of CLT panels to obtain the targets required to guide the robots for its machining. The method developed detects primitives geometries of the CLT panels, determines the appropriate operations (either sawing, drilling, or milling), select the robot based on manufacturing capabilities (reach and tool availability), and generates the target-path planning for its machining process. The proposed method is tested in a robotic machining station for CLT panels simulated in RobotStudio® as a case study. The results showcase the capabilities of the proposed algorithm to provide manufacturing results out of the process planning process from geometric information available at the design stage. These results include process duration, path planning, resource allocation and utilization. This study provides a framework to include manufacturing information in design decisions to facilitate planning or cost estimations and anticipate issues downstream generated during the design phase.

Influence Free Cash Flow and Growth Opportunity against Company Values with leverage as a Variable Intervening

The purpose of this research is to test and analyze the effect free cash flow and growth opportunities to company value with leverage as a variable intervening in textile and garment companies on the IDX in the 2019-2022 period. In this study the approach used by researchers is quantitative research and uses statistical formulas to help analyze the data and facts obtained. This data collection uses secondary data which can be taken from the Textile and Garment Sector companies listed on the IDX in the 2019-2022 period. The research model used ispath analysis. Data processing path analysis using program assistance IBM SPSS Statistics 25. The research results conclude Free Cash Flow not able to affect the value of the company (PBV), Free Cash Flow able to influence Leverage (THE), Growth opportunity (PER) is able to affect the value of the company (PBV), Growth opportunity (PER) is not able to influence leverage (THE), Leverage (DER) is not able to affect the value of the company (PBV), Leverage (DER) is not able to mediate the relationship between free cash flow to firm value (PBV), Leverage (DER) is not able to mediate the relationship between Growth Opportunity (PER) to firm value (PBV).

Scaling limits of loop-erased Markov chains on resistance spaces via a partial loop-erasing procedure

We introduce partial loop-erasing operators. We show that by applying a refinement sequence of partial loop-erasing operators to a finite Markov chain, we get a process equivalent to the chronological loop-erased Markov chain. As an application, we construct loop-erased random paths on bounded domains of resistance spaces as the weak limit of the loop erasure of the Markov chains on a sequence of finite sets approximating the space, and the limit is independent of the approximating sequences. The random paths we constructed are simple paths almost surely, and they can be viewed as the loop-erasure of the paths of the diffusion process. Finally, we show that the scaling limit of the loop-erased random walks on the Sierpiński carpet graphs exists, and is equivalent to the loop-erased random paths on the Sierpińksi carpet.

In situ measurement of austenite grain growth and recrystallization using laser ultrasonics

The development of next generation process models and advanced high-strength steel products for thin slab casting and direct rolling requires quantification of microstructure evolution during thermomechanical processing. Laser ultrasonics is a non-contact in-situ method to record grain growth, recrystallization and phase transformations in metals and alloys. Here, we will present an improved experimental design that facilitates a continuous microstructure measurement through the various stages of simulated hot rolling from reheating to runout table cooling using a Gleeble thermomechanical simulator equipped with a laser ultrasonics for metallurgy (LUMet) system. Austenite grain growth and static recrystallization after hot deformation are quantified based on attenuation of the ultrasound waves whereas austenite decomposition can be recorded with the changes in ultrasound velocity during the phase transformation. Further, the LUMet results for a microalloyed low carbon steel are validated with conventional techniques including optical and electron microscopy as well as double-hit tests. These experimental studies demonstrate the capabilities of laser ultrasonics in the identification of both normal and abnormal grain growth, non-recrystallization temperature, recrystallization, and austenite decomposition kinetics in a single test for a given processing path, as well as its potential for accelerated optimization of process control under industrial rolling conditions.

Research on Tolerance Optimization of High Precision Equipment Assembly Based on Error Transfer Prediction Model

In this paper, the assembly error transfer prediction model was established based on the error transfer attribute and the error transfer path of the assembly process. The assembly accuracy prediction was realized by combining error variation inequality, constraint inequality and mathematical statistics method. Aiming at the lowest processing cost of high-precision equipment assembly, the assembly accuracy required the reliability of index, the value interval of tolerance item and the principle of tolerance selection as constraints, the tolerance optimization model was established. The tolerance optimization of high-precision equipment assembly was carried out by combining the penalty function method and the improved genetic algorithm. Finally, taking gear oil pump assembly as an example, according to the reliability calculation formula of assembly accuracy, the reliability is 97.35%. Compared with the processing cost before and after optimization, the processing cost decreased by 12.13% after optimization, and the assembly accuracy reliability increased by 1.65%. The correctness and effectiveness of assembly accuracy prediction and tolerance optimization are verified.