Search

Previous studies have demonstrated that students who are engaged in learning tasks and make errors before receiving instruction on how to complete them, achieve better learning outcomes than students who first receive instruction and then complete the learning activities with the aim of avoiding errors. Although simulation literature often refers to errors as learning opportunities, to date, there is limited understanding of how pedagogical approaches that promote learning from errors can guide the design of simulation-based learning in healthcare education. To (a) present the Learning from Errors conceptual model; and (b) provide an example of how educators can use this model. The Learning from Errors model is drawn from critical elements of two pedagogical approaches, productive failure and error management training and pedagogical features of high-quality healthcare simulations. We describe the Learning from Errors model, which emphasises the need for adopting pedagogical methods that explicitly use errors as learning opportunities and ultimately inform simulation design. We then illustrate the application of this model to a simulation example. The model includes the following elements: i) normalisation of errors, ii) challenging simulation scenarios, iii) self-directed learning, iv) collaborative teamwork and v) comparison with best practice. This discussion paper presents the Learning from Errors conceptual model, an evidence-based approach that can assist educators in the design of simulations that embrace errors as a catalyst for learning. [ABSTRACT FROM AUTHOR]

Abstract: The flows of paper are analyzed throughout the papermaking processes, with the year 2007 and Korea defined as the system boundaries. In practice, the statistical data on the production, import and export of paper or pulp can be collected with relative ease from the government and industrial associations. However, the input data regarding the volumes of pulp and wastepaper used in different paper products, such as newsprint, printing papers, sanitary and household papers, specialty papers, and corrugating board base, are difficult to obtain because such information is generally kept confidential in the course of corporate operations. The production processes of paper products in Korea are modeled using information on raw materials, their compositions and production yields of products in order to identify and quantify the amounts of pulp and wastepaper used in each paper product. The material flows of paper are then analyzed based on the calculation model derived from the correlation of input and output flows between the individual processes throughout the entire paper lifecycle. Accuracy analysis using both mean absolute error (MAE) and mean absolute percent error (MAPE) is conducted to verify the amounts of pulp and wastepaper calculated from the proposed model against the volumes of domestically consumed pulp and wastepaper provided in the national statistics. Although the calculated values for the past (i.e., the 1980s and 1990s) differ to some degree from the statistical values, the data for the 2000s have a relatively higher level of accuracy, with the MAPE of the total pulp and recycling volume at 5.39% and 5.30%, respectively, thus validating the adequacy of the proposed modeling method. The proposed calculation model can be effectively used in the material flow analysis (MFA) of paper to reduce the burden of data collection and obtain relatively accurate results. [Copyright &y& Elsevier]

This paper is aimed at developing a systematic methodology for the cost-effective reduction of water usage and discharge in pulp and paper plants. As the industry moves towards increased system closure, the build-up of Non-Process Elements (NPEs) leads to serious consequences on the process equipment. In response, this paper achieves the following: • a mathematical model to track water and primary NPEs throughout the pulping process • rigorous targeting for water usage and discharge • a systematic framework for water reduction using mass integration strategies including no/low cost techniques as well as capital-based techniques • an optimisation model for the optimisation of allocation, recycle and separation of aqueous streams. A case study for water management in a kraft pulping process has been solved to highlight the usefulness of the devsied approach. [ABSTRACT FROM AUTHOR]

The article presents a conceptual framework using simulation to predict effluent biochemical oxygen demand (BOD) characteristics as a function of improved wastewater treatment. These simulations use equations that describe BOD kinetics. They also able to reproduce trends in f-ratio observed at various pulp and paper facilities and predict BOD reactivity as a function of treatment.

Within our research work we determined the Young's modulus distribution in the paper plane on the basis of results of tensile tests in selected directions. Using mathematical relationships valid for orthotropic materials, the moduli were calculated theoretically. The tensile stiffness orientation angle (TSA), and the TSO and TSI indices were also determined in order to define the deviations of the main axes of orthotrophy in the paper plane as determined by the machine and the cross directions. The calculation results were compared with measured values. They justified the conclusion that paper may be treated as an orthotropic material. [ABSTRACT FROM AUTHOR]

For the stability of composite fibre spinning, the difference in and distribution of the polymer melt velocity during the spinning are among the factors of importance. Based on the basic equation for the control of composite spinning dynamics, boundary conditions are identified and reported in this paper. A mathematical model for the symmetric and asymmetric distribution of the melt flow velocity in the microhole of the spinneret of the composite spinning assembly was developed. The accuracy of the mathematical model was also ascertained. It gives a theoretical basis for the designing of a composite spinning assembly. [ABSTRACT FROM AUTHOR]

We give a direct proof of the main result of the paper 'Homomorphisms with respect to a function' by K. Boulabiar and F. Gdara [1] without using the Axiom of Choice. [ABSTRACT FROM AUTHOR]

Abstract: The non-citation rate refers to the proportion of papers that do not attract any citation over a period of time following their publication. After reviewing all the related papers in Web of Science, Google Scholar and Scopus database, we find the current literature on citation distribution gives more focus on the distribution of the percentages and citations of papers receiving at least one citation, while there are fewer studies on the time-dependent patterns of the percentage of never-cited papers, on what distribution model can fit their time-dependent patterns, as well as on the factors influencing the non-citation rate. Here, we perform an empirical pilot analysis to the time-dependent distribution of the percentages of never-cited papers in a series of different, consecutive citation time windows following their publication in our selected six sample journals, and study the influence of paper length on the chance of papers’ getting cited. Through the above analysis, the following general conclusions are drawn: (1) a three-parameter negative exponential model can well fit time-dependent distribution curve of the percentages of never-cited papers; (2) in the initial citation time window, the percentage of never-cited papers in each journal is very high. However, as the citation time window becomes wider and wider, the percentage of never-cited papers begins to drop rapidly at first, and then drop more slowly, and the total degree of decline for most of journals is very large; (3) when applying the wider citation time windows, the percentage of never-cited papers for each journal begins to approach a stable value, and after that value, there will be very few changes in these stable percentages, unless we meet a large amount of “Sleeping Beauties” type papers; (4) the length of an paper has a great influence on whether it will be cited or not. [Copyright &y& Elsevier]

A method was developed to estimate the composition of deinked pulp or recovered paper in terms of hardwood kraft pulp, softwood kraft pulp, and mechanical pulp through analysis of the sugar units in hemicelluloses and pectins. Different pulps (i.e., bleached chemical pulp from hardwoods and softwoods and mechanical pulp) were obtained from different mills. The pulps were mixed in different proportions and dried. The content of arabinose, xylose, mannose, galactose, rhamnose, galacturonic acid, and 4-O-methyl-glucuronic acid, sugar units in hemicelluloses and pectins in the different pulps and in the mixtures were determined by acid methanolysis and gas chromatography. The contents of the sugar units were significantly different in the three pulp types but quite similar in the same pulp type, irrespectively of bleaching sequence. The modeling was performed using standard partial least squares regression (PLSR) and cross-validation using venetian blinds subsets. The data were autoscaled before regressions. The best model had two latent variables. The cumulative variation of X captured by the model was 0.988 (R²X), the cumulative variation of Y captured by the model was also 0.988 (R²Y), and the cumulative cross-validated variation of Y captured by the model was 0.974 (Q²). Accordingly, the PLS model is more than capable of predicting the validation set. It was concluded that the proportion of chemical pulp from hardwoods, chemical pulp from softwoods, and mechanical pulp can be estimated in recovered paper or deinked pulp using a mathematical model based on the content of selected sugar units in hemicelluloses and pectins. [ABSTRACT FROM AUTHOR]

The article discusses the study which develops a dynamic modular paper machine simulator package. It has been noted that computer simulation can be a valuable tool for the optimization of paper production processes, designing wastewater closure strategies and the visualization of a complicated process. It shows that by structuring the simulator as a set of modular blocks, a variety of configurations can be modeled by assembling the blocks in different ways. In addition, researchers have recommended that the simulator package can help in developing simple models for the simulation of complex dynamic systems.

This work is concerned with the determination of the adhesion strength between a paper web and an adhesive surface. Edvards- son et al. [Edvardsson, S., Gradin, P., and Isaksson, P., "On Dissipative Effects of Paper Web Adhesion Strength," Int. J. Solids Struct., Vol. 48(1), 2011, pp. 24-30] suggested recently a model that takes into account the energy dissipation caused by elastic-plastic deformation in the bent structure of a paper specimen. This model is fial'ther developed and investigated in the present work. A linear relation in plastic dissipation is discovered facilitating a novel analysis of the peeling tension and a more convenient determination of the proper adhesion strength. Industrial relevant examples are made with wet newsprint and kraft stock. A straightforward experimental procedure for determining the consistent adhesion strength is suggested. It is found that the agreement between the model and the experimental observations is good. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Saúde Pública is the property of Faculdade de Educacao da Universidade de Sao Paulo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: A lot of work has been done in the field of multi-valued model checking home and abroad. But some research works are not perfect. Some problems in the semantic definitions of temporal operators and corresponding model checking algorithms are found in the paper “Model Checking Using Partial Kripke Structure with 3-Valued Temporal Logic”. Some counterexamples are given to show these errors. On the basis of the discussion, some sound semantic definitions of temporal operators and correct algorithms of model checking for some temporal operators are given. [Copyright &y& Elsevier]

Abstract: Although the scale invariance is a main feature of growing networks, evidence from a few modelled networks show that the finite-size effect of network at a fixed time cannot be ignored. We propose a concept of time-dependent scale-free networks, and prove the criteria for the stability and scale-free of growing networks by the degree-growing Markov chain. Our results show the importance of rigorous theoretical analysis for the network science. [ABSTRACT FROM AUTHOR]

Copyright of Revue Française de Sociologie is the property of Presses de Sciences Po and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper introduces a novel pseudo-random sequence generator, applicable across all uses of pseudo noise (PN)-sequence. The proposed generator, coined as the circular pseudo-random signal generator, embodies a unique fusion of graphical representation and mathematical modeling. The cornerstone of this method is its capability to offer variable configurations in pseudo-random sequence generation, enabling the adaptive operation of the pseudo-random sequence between the transmitter and the receiver. Uniquely, the circular pseudo-random Sequence Generator can generate pseudo-random sequences of varying lengths, with practical implementation feasible through multiple methodologies, including microcontrollers or field-programmable gate array (FPGA) technology. Consequently, the paper endeavors to elucidate the mathematical model of generation, supplemented with illustrative examples, and demonstrate the real-world implementation using FPGA technology. With broad applicability, this sequence generator is well-suited to all applications requiring such a generator, notably in security applications and pilot generations. [ABSTRACT FROM AUTHOR]

The massive Internet of Things (IoT) comprises different gateways (GW) covering a given region of a massive number of connected devices with sensors. In IoT networks, transmission interference is observed when different sensor devices (SD) try to send information to a single GW. This is mitigated by allotting various channels to adjoining GWs. Furthermore, SDs are permitted to associate with anyGWin a network, naturally choosing the one with a higher received signal strength indicator (RSSI), regardless of whether it is the ideal choice for network execution. Finding an appropriate GW to optimize the performance of IoT systems is a difficult task given the complicated conditions among GWs and SDs. Recently, in remote IoT networks, the utilization of machine learning (ML) strategies has arisen as a viable answer to determine the effect of various models in the system, and reinforcement learning (RL) is one of these ML techniques. Therefore, this paper proposes the use of an RL algorithm for GW determination and association in IoT networks. For this purpose, this study allows GWs and SDs with intelligence, through executing the multi-armed bandit (MAB) calculation, to investigate and determine the optimal GW with which to associate. In this paper, rigorous mathematical calculations are performed for this purpose and evaluate our proposed mechanism over randomly generated situations, which include different IoT network topologies. The evaluation results indicate that our intelligentMAB-based mechanism enhances the association as compared to state-of-the-art (RSSI-based) and related research approaches. [ABSTRACT FROM AUTHOR]

The red palm weevil is one of the most dangerous pests affecting date palm trees in the Gulf region and the Middle East. This paper investigates the control of the red palm weevil (RPW) in date palms using several techniques, namely stem injection, sex pheromone traps, and the Sterile Insect Technique. A mathematical model describing the spread of the red palm weevil is presented, and the boundedness of the solution for the RPW system is studied. The conditions for local stability, forward bifurcation, and Hopf bifurcation are also obtained. Additionally, this research highlights the significance of optimal control in managing RPW and simulates the model using the Forward-Backward Sweep numerical method. It is observed that the parameters of the sterile insect technique, the pheromone trap, and the mechanical injection play important roles in controlling the RPW. Mechanical Injection may be more effective in controlling the palm weevil compared to the other two methods. [ABSTRACT FROM AUTHOR]

The significance of mental health inequities globally is illustrated by higher rates of anxiety and depression amongst racial and ethnic minority populations as well as individuals of lower socioeconomic status. The COVID-19 pandemic has further exacerbated these pre-existing mental health inequities. With rising mental health concerns, arts engagement offers an accessible, equitable opportunity to combat mental health inequities and impact upstream determinants of health. As the field of public health continues to shift its focus toward social ecological strategies, the social ecological model of health offers an approach that prioritizes social and structural determinants of health. To capture the impacts of arts engagement, this paper creates an applied social ecological model of health while aiming to advocate that engaging in the arts is a protective and rehabilitative behavior for mental health. [ABSTRACT FROM AUTHOR]

Community health workers (CHWs) and promotores de salud are frontline health workers who typically come from the communities they serve. Despite providing crucial services, they are not institutionalized (or integrated) within much of the U.S. health care system. Many work, either officially or unofficially, as medical interpreters--restricting their full impact as CHWs/promotores. In this paper, we detail the misemployment and its effects among a subsample of CHWs/promotores in two geographically distinct, exploratory projects. We encourage that collaborative research with CHWs/promotores continue and that fidelity to the CHW model be ensured to realize their true potential. [ABSTRACT FROM AUTHOR]

The article analyses the evolution of mathematical models used in life cycle estimation. A comparison between the different mathematical models and their areas of applicability is proposed. This analysis is generally done in terms of costs. The importance of the article lies in the proposal of a new mathematical model for estimating life cycle of power substations, compatible with current and future requirements. The study findings reveal that an optimization model can be established using the life cycle assessment method to obtain a longer lifespan, but also to minimize costs (maintenance, repairs, replacements, etc.). In order to establish a mathematical model of the life cycle of electrical substations, it is necessary to study several important design parameters and decision factors for each stage of the life cycle. Even if the paper does not provide empirical results, it must prove that it is necessary to develop a multi-algorithm optimization framework to find an adequate solution. The life cycle must be modelled according to: equipment availability technological evolution, maintenance activities, risk management, environmental protection, human error, etc. The study helps further research to build, implement and validate a robust model with development possibilities depending on the needs of the researchers. [ABSTRACT FROM AUTHOR]

Over the last decades increased use of waste paper as a source of fibre for the pulp and paper production process has meant that the industry has undergone significant changes in material and energy use. However, this means use of technologies that do not generate a significant amount of biomass for energy recovery, and thus requires that more energy is purchased by the industry. If waste paper is incinerated instead of repulped, energy purchases by society can be reduced, which will have a positive effect on CO2 emissions. In this article, we argue that an analysis of these effects requires a systems analytical approach including the different production lines, fibre flows and alternative uses of the fibre rather than a life cycle analysis with allocation methods. In the latter case, one often looks at just one production process and uses allocation methods for in- and outflow from or to other processes. We show that allocation methods sometimes used in life cycle analyses do not give a good approximation. Thus, it is recommended that allocation be avoided by, for example, expanding the system. If allocation cannot be avoided, the allocation should be based on the way in which the inputs and outputs are changed by quantitative changes in the products or functions delivered by the system. [ABSTRACT FROM AUTHOR]

This paper presents a conceptual framework that combines technology-based instruction and mathematical modeling in a STEAM-oriented approach to enhance the English language acquisition of Malaysian students. The proposed framework consists of a six-month English as a Foreign Language program that integrates technology and mathematical simulation in a STEAMoriented methodology. The exercises are designed to enhance linguistic competence, with a focus on improving listening, speaking, reading, and writing skills. The framework aims to foster a positive learning environment that encourages self-determination and promotes sociocultural interaction. The integration of technology-enabled instruction and mathematical modeling offers a viable strategy for enhancing the language competency of non-native English speakers. However, further research and empirical analysis are necessary to evaluate the impact of this framework on academic performance. Despite this limitation, the proposed framework offers a promising approach to address the challenges faced by less proficient Malaysian students in acquiring English language skills. In conclusion, this paper presents a conceptual framework that integrates technology-based instruction and mathematical modeling in a STEAM-oriented approach to enhance the English language acquisition of less proficient Malaysian students. The framework is grounded in sociocultural and self-determination theoretical perspectives and aims to create a positive learning environment that promotes linguistic competence. [ABSTRACT FROM AUTHOR]

Robust and transparent formal benefit-risk (BR) analyses for medicinal products represent a means to better understand the appropriate use of medicinal products, and to maximize their value to prescribers and patients. Despite regulatory and social imperatives to conduct structured BR (sBR) assessments, and the availability of a plethora of methodological tools, there exists large variability in the uptake and execution of sBR assessments among pharmaceutical companies. As such, in this paper we present an sBR assessment framework developed and implemented within a large global pharmaceutical company that aims to guide the systematic assessment of BR across the continuum of drug development activities, from first-time-in-human studies through to regulatory submission. We define and emphasize the concepts of Key Clinical Benefits and Key Safety Risks as the foundation for BR analysis. Furthermore, we define and foundationally employ the concepts of sBR and a Core Company BR position as the key elements for our BR framework. We outline 3 simple stages for how to perform the fundamentals of an sBR analysis, along with an emphasis on the weighting of Key Clinical Benefits and Key Safety Risks, and a focus on any surrounding uncertainties. Additionally, we clarify existing definitions to differentiate descriptive, semi-quantitative, and fully quantitative BR methodologies. By presenting our framework, we wish to stimulate productive conversation between industry peers and health authorities regarding best practice in the BR field. This paper may also help facilitate the pragmatic implementation of sBR methodologies for organizations without an established framework for such assessments. [ABSTRACT FROM AUTHOR]

This paper presents a multi-objective mathematical model to optimize and harmonize a supply chain in order to reduce costs, improve quality, and gain a competitive advantage and position using meta-heuristic algorithms. The purpose of optimization in this field is to enhance both quality and customer satisfaction and reduce the production time and related prices. The present research simultaneously optimized the supply chain in the multi-product and multi-period modes. The presented mathematical model was first validated. The parameters of the proposed algorithm were then adjusted to solve the model using Multi-Objective Simulated Annealing (MOSA) algorithm. To validate the performance of the designed algorithm, some examples were solved based on General Algebraic Modeling System (GAMS). The MOSA algorithm achieved average errors of %0.3, %1.7, and %0.7 for the first, second, and third objective functions, respectively, in the average less than one minute. The average time to solve was 1847 seconds for the GAMS software; however, the GAMS failed to reach an optimal solution for large problems in a reasonable computational time. The average error of the designed algorithm was less than 2% for each of the three objectives under study. These show the effectiveness of the MOSA algorithm in solving the problem introduced in this paper. [ABSTRACT FROM AUTHOR]

This paper discusses a particular situation in project management in which an analyst attempts to prioritize several independent activities to handle all of them one by one in such a way that there would be no precedence relationships over the activities. The novelty of this research is that the structure of prioritized activities is linear in arrangement which can be considered as a combinatorial optimization problem. The paper formulates a mathematical model and applies it to two real cases in the oil and gas industry. In addition, a row generation procedure is developed to solve largescale problems and the computational results for the problem instances of size up to 300 activities are reported. The results demonstrate the applicability and efficiency of the proposed methodology. [ABSTRACT FROM AUTHOR]

An integrated decision in supply chain is a significant principle for proper competition in today's market. This paper proposes a novel mathematical model in a two-stage supply chain scheduling to make a coordination between procurement and manufacturing activities. The supply chain scheduling along with the production approach of cellular manufacturing under demand, processing time, and transportation time uncertainties makes business environment sustainably responsive to the changing needs of customers. Uncertainties are formulated by queuing theory. In this paper, a new mixed-integer nonlinear programming formulation is used to determine types of vehicles to carry raw materials, suppliers to procure, priority of each part in order to process, and cell formation to configure work centers. The goal is to minimize total tardiness. A linearization method is used to ease tractability of the model. A genetic algorithm is developed due to the NP-hard nature of the problem. The parameters of the genetic algorithm are set and estimated by Taguchi's experimental design. Numerous test problems are employed to validate the effectiveness of the modeling and the efficiency of solution approaches. Finally, a real case study and a sensitivity analysis are discussed to provide significant managerial insights and assess the applicability of the proposed model. [ABSTRACT FROM AUTHOR]

Copyright of Revista Interuniversitaria de Formación del Profesorado is the property of Asociacion Universitaria de Formacion del Profesorado (AUFOP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, harmonic resonance analysis of the grid comprising Wind Power Plants (WPPs) with Permanent Magnet Synchronous Generators (PMSGs) is presented. Usually, Norton equivalent circuit is used as the Wind Turbine (WT) model for harmonic resonance studies, in which the WTs are simply modeled as ideal current and voltage sources and the impacts of converters controls on the WTs output impedances are neglected. This paper deals with the harmonic resonance analysis of the WPP system by considering the impacts of converters controls and current and voltage measurement filters. In doing so, harmonic impedance models of the WTs are presented for simple and detailed cases. Then, the WT harmonic impedance is extracted for the mentioned cases. Next, the results of frequency scan and harmonic mode resonance analyses for different cases are given and compared. Then, the effects of the current and voltage measurement filters and WT converter control on harmonic resonance analysis of the study WPP system are presented. It is shown that increasing the bandwidth of the grid-side converter current control loop cannot shift the resonant frequencies, but it certainly enhances the system damping and, consequently, reduces the driving point impedances in the resonant frequencies. [ABSTRACT FROM AUTHOR]

Emerging Industry 5.0 pushes advanced automation towards resilient solutions with enhanced human role. Resilience as an ability to sustain processes in the face of disruptions and adversarial attacks requires careful modelling and simulation. Cellular automata are efficient mathematical models used to simulate the behavior of complex systems, which change their state based on a set of predefined rules. In this paper, we suggest several updates to cellular automata (particularly Conway's "Game of Life") to address resilience. These include "Life and Creation", "War and Peace", and their hybrid "War and Creation" capable of addressing the important components of resilience, such as controllable creativity and adversarial interactions. Inherited in these updates and known advantages of cellular automata, such as simplicity, emergent behavior, parallelism, and adaptability, makes it a powerful simulation tool for a wide range of Industry 5.0 systems that involve humans, smart infrastructure, their complex and adversarial interactions, safety, and resilience. [ABSTRACT FROM AUTHOR]

With the rapid growth of Internet applications, massive demand for cloud services has brought challenges to data center networks (DCNs). Traditional wired DCNs adopt multilayer structure, leading to the congestion in high-layer switches. Furthermore, complex cabling in wired DCNs affects the flow of cold air, reduces the cooling efficiency, and increases energy consumption. To solve these problems, in this paper, we introduce an architecture for intra-DCN based on free space optic (FSO) wireless communication. The proposed scheme exploits spatial position of FSO transceivers at different heights to realize obstruction-free transmission for inter-rack requests. We formulate the transceiver arrangement problem into a mathematical model while satisfying the requirement for direct line-of-sight communication between any pair of transceiver nodes. Moreover, we evaluate the network performance of the proposed scheme via simulation in terms of flow completion time, server throughput, and power consumption. Compared with traditional ones, our scheme can considerably decrease power consumption while obtaining better network performance. [ABSTRACT FROM AUTHOR]

Industrial clusters are one of the most current development models. Aggregation of firms in a geographical area has many advantages, such as cost reduction, better supply, and knowledge emission with linkage together. The linkage result will be created the networks. The industrial clusters without co-operation networking will not be developed. That must be noticed to severe changes of business environment parameters. Therefore, this paper develops an uncertain mathematical model under sustainable and dynamic conditions. The model contains four objectives, namely profit, transportation cost, employment, and environment appraisal of the cluster. The outcome of this research is to find the best/optimal solution for firms’ arrangements with/within networks that maximize the profit, employment, and environment score and so minimize the transportation cost. The assignment patterns show horizontal and vertical cooperation with/within networks. The efficiency of model clustering in sub-clusters is followed by the neighbor clustering efficiency and the one’s clustering efficiency methods. [ABSTRACT FROM AUTHOR]

This research paper focuses on the development of advanced mathematical models for disease diagnosis and prediction, and the subsequent creation of automated systems based on these models. These systems leverage a range of mathematical models and incorporate cutting-edge information technology achievements to provide medical professionals with valuable decision-making support. By amalgamating mathematical rigor and technological innovation, this research endeavors to enhance the accuracy and efficiency of medical diagnoses, thereby improving patient care and healthcare outcomes. This study delves into the persistent need for contemporary information systems, where information plays a crucial role in decision-making. It aims to provide an objective approach to addressing pressing medical challenges, particularly in disease diagnosis and prediction, enhancing the effectiveness of these critical tasks. Automated medical information systems, built on advanced mathematical models, significantly empower physicians. Machine diagnostics, relying on deterministic logic, the phase interval method, and information-probabilistic logic, bolster diagnostic capabilities. Functional entropy enables individuals to handle vague information, aiding decision-making. Assessing imprecision and uncertainty computationally diminishes subjectivity, while employing fuzzy set theory enhances diagnostic modeling. Mathematical models assess diagnostic indicators, and linguistic variables quantify resemblance. The diagnostic model for primary biliary cirrhosis and active hepatitis utilizes a diagnostic table and gradient projection. This comprehensive study advances medical diagnostics through mathematical models and automated systems, addressing critical healthcare challenges. [ABSTRACT FROM AUTHOR]

In the present paper, an attempt is made to construct a deterministic mathematical simulation for population systems, by which their temporal (equation of motion) and spatiotemporal (equation of distribution) behaviour can be deduced, as solutions of the constitutional differential equations of the system. The generic formulation of the constitutional equations gives the simulation the possibility to expand to several populations, but also to parameters of different nature (say economic), by applying proper transformations according to the inner properties of each parameter. The introduction of the topographical features of such a system can be reduced to a boundary conditions problem, applied to the constitutional differential equations. Two initial applications are analyzed herein, namely a one-dimensional inertial population system, and a one-dimensional dynamic population system, where the external force corresponds to a space of constant curvature. The theoretically predicted behaviors of the population distribution of these systems are compared qualitatively to actual field data, collected from cities around the World. [ABSTRACT FROM AUTHOR]

The electric vehicle battery state prediction in real time is an important issue to avoid the risks of burning the battery due to over-charging or dead batteries that are caused by aging. Based on the past works, it is found that the State of Charge (SOC) can be predicted, while predicting the State of Health (SOH) is a difficult challenge. Usually, the SOH is predicted after the end of the driving or the charging cycle under constant conditions; this method is practically impossible because the battery can reach the end of the battery life before achieving the prediction process. In this paper, a SOH prediction method is proposed based on SOC prediction because there is a relation between the SOC and the SOH as indicated by deriving a mathematical model. The prediction process of battery age is achieved during the beginning of the battery charging process under constant conditions of charging, in which a SOC estimation has been implemented by the nonlinear auto-regressive with exogenous input neural network (NARX) with two initial values of SOC, the default value (0%) and practical value (10%) and two charging current rates (0.5C and 1C). The proposed method has been simulated by MATLAB, which several scenarios have been achieved to validate the proposed method. The root-mean-square error (RMSE) values are very promising for both predicting SOC and SOH that are 0.5% and 0.018%, respectively. [ABSTRACT FROM AUTHOR]

The classical manufacturing systems assume that all produced items are of perfect quality. They also need to consider the rework process in manufacturing operations. Moreover, most of the previous literature considers single-stage production-inventory systems and does not consider multi-stage options. However, in real-world production-inventory systems, defective items are inevitable, and a fraction of the produced items may be defective. In addition, to avoid extra costs and consider environmental issues, organizations tend to rework activities. We propose single and multi-stage production-inventory systems in manufacturing operations where the process is defective, rework is possible, and a percentage of items are scrapped. A main assumption in the current paper is that the defective rate is assumed to be an uncertain parameter. The grey systems theory, as a mathematical tool to address uncertain information in real-world situations, is utilized to model the random defective rate via a grey nonlinear programming problem. The proposed issues are investigated via numerical examples to assess the impact of grey parameters on optimal solutions. [ABSTRACT FROM AUTHOR]

The article focuses on the prediction of the tensile breaking strength, the most commonly used physical property for paper characterization. It develops a novel three-dimensional computational simulator of paper structure to better understand the influence of fiber morphology on paper properties. It also discusses the development of the tensile strength model.

Extending metaphorically the Moisilean idea of ‘nuanced-reasoning logic’ and adapting it to the e-world age of Information Technology (IT), the paper aims at showing that new logics, already useful in modern software engineering, become necessary mainly for Multi-Agent Systems (MAS), despite obvious adversities. The first sections are typical for a position paper, defending such logics from an anthropocentric perspective. Through this sieve, Section 4 outlines the features asked for by the paradigm of computing as intelligent interaction, based on ‘nuances of nuanced-reasoning’, that should be reflected by agent logics. To keep the approach credible, Section 5 illustrates how quantifiable synergy can be reached - even in advanced challenging domains, such as stigmergic coordination - by injecting symbolic reasoning in systems based on sub-symbolic ‘emergent synthesis’. Since for future work too the preferred logics are doxastic, the conclusions could be structured in line with the well-known agent architecture: Beliefs, Desires, Intentions. [ABSTRACT FROM AUTHOR]

A modular, steady-state model for the recovery furnace (WinFURN) has been extended to predict dust compositions and amounts accurately The model is validated with industrial boiler data from three recovery boilers using the same inlet black liquor but having different combustion air systems, generating different furnace temperatures The model can predict the differences in dust compositions and amounts among the three boilers. [ABSTRACT FROM AUTHOR]

Presents a summary of peer-reviewed papers in the August 2004 issue. Purpose of biochemical pulping; Effect of substituting aspen-high yield pulp for hardwood kraft pulp in fine papers on alkyl ketene dimer; Mathematical model that can predict the buildup of dissolved solids in closed white water system.

Current production structures require large amounts of primary materials and are not likely to be sustained without large implications for the environment. A good understanding of societal metabolism is likely to contribute to more sustainable production and consumption. Material flow analysis (MFA) intends to support this understanding by providing insight in material flows. In this article a new method for analyzing materials flows, called STREAMS, is tested. The method is applied to analyze the paper and wood flow through the economic system of The Netherlands. The method is based on data available from the so-called supply and use tables; these tables are made available by Statistics Netherlands and describe the economy of a country in terms ofannual supply and use of goods and services by industries and consumers. The method proves to be very useful in analyzing the paper and wood flow in The Netherlands. The method provides detailed informationabout the final consumption of paper and wood, even for packaging materials and product parts made out of paper and wood. Trends are visible that statistical offices collect less physical data about material flows. This will make the construction of material flow analyses like this one more difficult in the future. [ABSTRACT FROM AUTHOR]

The optimization of train formation plan is a large-scale combinatorial optimization problem, which is difficult to solve. This paper mainly studies the optimization algorithm of the single-block train formation plan. The corresponding mathematical model is established by consulting relevant literature, and a positive feedback search algorithm based on absolute conditions is proposed. First of all, the wagon flow that meets the absolute conditions directly runs through train flow without making other choices. For the wagon flow that does not meet the absolute conditions, select the target station to reach directly according to the probability. The probability of wagon flow selecting a station is calculated according to the pheromone of the wagon flow at the station. At the same time, a pheromone update strategy with positive feedback mechanism is proposed to make the search process converge. Finally, the feasibility of the algorithm and the necessity of introducing absolute conditions into the algorithm are verified by taking eight technical stations in the linear direction of the road network as examples. [ABSTRACT FROM AUTHOR]

This study focuses on an artery with multiple stenoses, emphasizing the electro-osmotic effects. The artery's walls are porous, and slip boundary effects are present. Blood ow problems are better modeled with a slip and porous border. It is examined extensively due to the wide range of applications in the medical field, especially in diagnosing drug delivery and handling cellular irregularities. In this paper, we have visualized the non-Newtonian behavior of blood by using viscoelastic fluids as Williamson's fluid model. A mathematical model for an incompressible fluid is created, and the mathematical issue is then transformed into its dimensionless form by applying limitations in the case of mild multiple stenoses. The partial differential equations for the velocity and temperature profiles can be found when the problem is put into a dimensionless form. Analytical solutions of the resulting system are calculated with the help of the Homotopy Perturbation Method (HPM). The visual representation of analytically obtained solutions is investigated for both symmetric and non-symmetric geometries of stenosis. For varied values of ow rate Q and electro-osmotic parameter m, the streamlines are examined in detail. [ABSTRACT FROM AUTHOR]

Oil waste is one of the most important pollutants in the oil and gas industry. Since the oil owing in the wells contains significant amount of saltwater, the effluent amount rises upon increasing the oil reservoir extraction. Separating the saltwater from the extracted oil before starting the refinery process plays an essential role in reducing the oil costs and benefiting from the transfer capacity as well. This paper presents a new Chapman-Kolmogorov Equation-Based (CKEB) method to evaluate the availability of a desalination system with three-state equipment and weighted-k-out-of-n configuration. In this system, the equipment is repairable, and each repair facility can repair all equipment types of different sub-systems (pump stations). All failures and repairs were considered to have a constant rate (with exponential distribution) and use the Chapman-Kolmogorov equations to drive the system availability. Then, the presented method was validated using a simulation technique. Finally, the elapsed times of solving both techniques were calculated and compared. The results confirmed the superiority of the CKEB technique in terms of computational time. Compared with the simulation technique, the computational time ratio for the CKEB method was in the range of 0:0002%0:0058% for the small-size problems, 0:05%0:94% for the medium-size problems, and 1.31%-5.39% for the large-size problems. [ABSTRACT FROM AUTHOR]

The recent outbreak of rabies virus has affected numerous individuals in the community, highlighting the importance of studying the disease mathematically in epidemiology. In this paper, we develop a mathematical model for the spread of rabies disease using the harmonic mean incidence rate and determine the reproduction number R 0 using the next generation matrix approach. The fractional dynamics of the model incorporate the interaction between infected individuals and environmental factors. We analyze the model using both Atangana-Baleanu-Caputo (ABC) and Caputo-Fabrizio (CF) techniques, drawing on both modern and classical approaches. For qualitative investigation using fractional operators, we utilize the Banach fixed-point theory and derive the Hyers-Ulam stability concept. We assign values to the model parameters and utilize the Newton interpolation technique to obtain a numerical scheme. Additionally, we perform sensitivity analysis on the model. In conclusion, our findings provide important insights for the study of epidemics. [ABSTRACT FROM AUTHOR]

Copyright of Paradigma is the property of Universidad Pedagogica Experimental Libertador and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)