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ABOUT ICMSOA2022Organized by Yaseen Academy, 2022 The 2nd International Conference on Modeling, Simulation, Optimization and Algorithm (ICMSOA 2022), which was planned to be held during 11-13 November, 2022 at Sanya, Hainan Province, China. Due to the travel restrictions caused by covid, the participants joined the conference online via Tencent Meeting at 12 November, 2022. The Conference looks for significant contributions to related fields of Modeling, Simulation, Optimization and Algorithm. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.CALL FOR PAPERSPlease make sure your submission is in related areas of the following general topics. The topics include, but are not limited to:Simulation modeling theory and technology, Computational modeling and simulation, System modeling and simulation, Device/VLSI modeling and simulation, Control theory and applications, Military Technology Simulation, Aerospace technology simulation, Information engineering simulation, Energy Engineering Simulation, Manufacturing Simulation, Intelligent engineering simulation, Building engineering simulation, Electromagnetic field simulation, Material engineering simulation, Visual simulation, Fluid mechanics engineering simulation, Manufacturing simulation technology, Simulation architecture, Simulation software platform and Intelligent Optimization Algorithm, Dynamic Programming, Ant Colony Optimization, Genetic Algorithm, Simulated Annealing Algorithm, Tabu Search Algorithm, Ant Colony System Algorithm, Hybrid Optimization Algorithm in other related areas.The conference was begun at 10:00am, ended at 17:30am, 12 November, 2022. There were 77 participants in total, 2 keynote speakers and 17 invited oral speakers, Assoc. Prof. Jinyang Xu from Shanghai Jiaotong Univeristy in China and Dr. Victor Koledov from Innowledgement GmbH in Germany delivered their keynote speeches, each speech cost about 50 minutes, including the questions&discussion time.On behalf of the conference organizing committee, we'd like to acknowledge the unstinting support from our colleagues at Yaseen Academy, all Technical Program Members, speakers, reviewers, and all the participants for their sincere support.Conference Organizing CommitteeICMSOA 2022List of Conference General Chair, Program Chair, Conference Committee Chair Members, International Technical Committee Members, International Reviewers are available in this Pdf.
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Traditional retailers (bricks-and-mortar) have been continuously increasing online sales. However, not all retail companies were able to respond to the increasing sales with the same efficiency level as their competitors. This paper aims to propose a dynamic model – incorporating principles of Optimal Control Theory (OCT) into a Data Envelopment Analysis (DEA) model - for measuring the performance of retailing companies' cost efficiency. It also aims to contribute through the application by investigating the impact of the pandemic on companies from the most prominent developing market in Latin America, Brazil. Twenty-one companies publicly traded in the São Paulo Stock Exchanges (B3) between the third quarter of 2018 (3Q2018) and the third quarter of 2020 (3Q2020) were investigated. Also, six measures - initial inventory cost (IIC), final inventory cost (FIC), net operating income (NOI), cost of goods sold (COGS), cost of the purchased product (CPP), and plant, property, and equipment (PPE) – were considered. In this way, the findings have implications for researchers and practitioners. Practitioners can discover which competitor(s) is (are) adopting the best practices at each operational aspect (e.g., inventory cost). Additionally, the proposed method can be replicated in other markets (developing or not) and for other categories of retailing companies (e.g., small- and middle-sized). Further research directions are presented, and their implications are discussed.
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Through addressing female academics in three public universities in Egypt, we aim to find out the extent to which female academics prefer to continue working from home (WFH) as a means of fulfilling their job responsibilities and the determinants for accepting or rejecting that option. A qualitative research method through semi-structured interviews with 33 female academics from three public universities selected from among 26 public institutions of higher education in Egypt. Moreover, our findings show that the preference to continue working from home varies across the addressed female academics, as they all differ in terms of workload, psychological well-being and the level of authority, control, and autonomy they have over their job. Furthermore, we identified familial commitments, availability of the information and infrastructure needed for work, cohesiveness when adopting WFH, and the extreme level of work from home as the four main determinants shaping the preferences of female academics in regard to working from home. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
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Within the context of the current global economic crisis, employees generally have a high level of fear that may lead them to use unethical pro-organizational behavior (UPB) to increase their sense of control. We used self-control theory to explore the mechanisms and boundary conditions of employees' fear of external threats and how this affects their levels of UPB. We conducted a twowave survey of 544 finance personnel in China. The results indicated that fear of external threats was positively correlated with UPB and that sense of control mediated this relationship. Perceived ethical climate reinforced the negative relationship between sense of control and UPB, which, in turn, weakened the positive effect of participants' sense of control, whereas fear of external threats increased the incidence of UPB. Implications are discussed.
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Elementary control theory and epidemic spread models illustrate the deadly impacts delay in recognizing pandemic threat and failure of institutional cognition in facing that threat can have on the institutions of public health. While short delays may cause some oscillation that rapidly dies out, sufficiently large time gaps trigger multiple infection waves of increasing severity, much like the onset of a power network blackout or of uncontrollable vehicle fishtailing. Similar-and synergistic-oscillations are found to be triggered by sufficiently low rates of institutional cognition. This approach begins to lift the cultural constraints inherent to host-pathogen population dynamics models of infectious disease in social systems sculpted by the synergisms of geography, power relations, and path-dependent historical trajectory. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. All rights reserved.
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Covid19 has infected many individuals around the world, this virus is spreading rapidly. In the context of controlling and handling the spread of COVID-19, appropriate strategies and policies are needed, mathematics will play a very important role in this problem, especially to provide information about this with an understanding of the dynamics of the transmission of this covid virus. To suppress the spread of the Covid-19 virus which is currently hitting, several countries have implemented large-scale social restrictions. To identify the best approach to reduce of this Covid-19 disease spreading at minimal cost, we developed a mathematical model of the covid 19 virus by implementing large-scale social restrictions and applying optimal control theory. We provide two types of control: the first is in the form of an education campaign about covid-19 and an awareness program, and the second is in the form of a quarantine program. Compared with no optimal control, giving optimal control can provide a more significant reduction in the number of populations S, Sr, O, P, I and increase the number of individual populations that recover more significantly.
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In this article, Euler's technique was employed to solve the novel post-pandemic sector-based investment mathematical model. The solution was established within the framework of the new generalized Caputo-type fractional derivative for the system under consideration that serves as an example of the investment model. The mathematical investment model consists of a system of four fractional-order nonlinear differential equations of the generalized Liouville–Caputo type. Moreover, the existence and uniqueness of solutions for the above fractional order model under pandemic situations were investigated using the well-known Schauder and Banach fixed-point theorem technique. The stability analysis in the context of Ulam—Hyers and generalized Ulam—Hyers criteria was also discussed. Using the investment model under consideration, a new analysis was conducted. Figures that depict the behavior of the classes of the projected model were used to discuss the obtained results. The demonstrated results of the employed technique are extremely emphatic and simple to apply to the system of non-linear equations. When a generalized Liouville–Caputo fractional derivative parameter (ρ) is changed, the results are asymmetric. The current work can attest to the novel generalized Caputo-type fractional operator's suitability for use in mathematical epidemiology and real-world problems towards the future pandemic circumstances.
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There are many inevitable disruptive events, such as the COVID-19 pandemic, natural disasters and geopolitical conflicts, during the operation of the container port supply chain (CPSC). These events bring ship delays, port congestion and turnover inefficiency. In order to enhance the resilience of the CPSC, a modified two-stage CPSC system containing a container pretreatment system (CPS) and a container handling system (CHS) is built. A two-dimensional resilience index is designed to measure its affordability and recovery. An adaptive fuzzy double-feedback adjustment (AFDA) strategy is proposed to mitigate the disruptive effects and regulate its dynamicity. The AFDA strategy consists of the first-level fuzzy logic control system and the second-level adaptive fuzzy adjustment system. Simulations show the AFDA strategy outperforms the original system, PID, and two pipelines for improved dynamic response and augmented resilience. This study effectively supports the operations manager in determining the proper control policies and resilience management with respect to indeterminate container waiting delay and allocation delay due to disruptive effects.
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Purpose: The study examined whether parental care and family support moderate the association between school bullying victimization and cyberbullying victimization among college students by applying the social anthropological approach and social control theory Method: Data were collected for 261 college students (57.9% female) aged between 18 to 24 or older from a university in the Midwest region of the United States. A latent moderated structural equations approach was utilized Results: The data revealed that bullying victimization was positively associated with cyberbullying victimization. Moreover, parental care was a significant moderator between bullying victimization and cyberbullying victimization Discussion: These findings have implications of preventing victims of bullying becoming victims of cyberbullying. Parental involvement especially needs to be emphasized for college students' cyberbullying prevention and intervention programs. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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In the last month of 2019, a new version of Corona disease was observed in Wuhan (China) which is known as Covid-19. Several models have been proposed to predict disease treatment. The SIR model is considered one of the simplest models for the prediction of pandemic disease. This means susceptible (S), infected (I), and recovered (R) populations. The SIRD model is yet another method that includes one more equation, i.e., the number of deaths (D). This paper proposed a control law for the first time to prevent the progression of the disease. The proposed control law is based on the SIRD model and uses the feedback linearization method for the Covid-19 nonlinear model. The goal of control in this model is to reduce the number of people infected with the Covid-19 and the number of deaths due to the disease. Delay in treatment of infected people and percentage of people who should be treated are investigated as two important parameters. The results show that with the treatment of infected people in the first weeks, the number of people infected decreases by 96.3% and the number of deaths by 93.6% © 2022 IEEE.
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A pandemic can wreak havoc in supply chains, as witnessed in the COVID-19 context. As workers get infected, production level drops and demand from customers goes unfulfilled. Combining in a novel way an epidemic model with optimal control theory, our model provides a plant manager with the optimal level of prophylactic effort she needs to deploy over a planning horizon to protect the workforce from a pandemic in its early stage and so maintain production levels. Given the production planning problem, the effort in terms of prophylactic measures can be optimally determined in closed form, balancing worker protection against production requirements in a single step. The manager must initially implement the strictest measures before relaxing them in time. Three extensions are presented:, (1) determine the optimal period of time over which the prophylactic measures should be maintained;(2) determine the optimal effort in terms of prophylactic measures in the case of an endemic disease;and (3) assess the effect of a stochastic exogenous shock on the total number of infected. This research provides a production planning model that allows a decision-maker to mitigate the impact of worker absenteeism at the onset of a pandemic, thus improving supply chain resilience.
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The aim of the study is to examine whether and how emotional intelligence and aggression vary with gender and urban-rural area in South Africa. A cross-sectional design was used. A total of 440 adolescents aged between 13-18 years old participated in the study. Stratified sampling method was used in the selection of participants. Emotional Intelligence Questionnaire and Aggression Questionnaire were used to measure emotional intelligence and aggression. The study hypotheses were tested using logistic regression analysis. Emotional intelligence varies with gender. Males managed other peoples emotions better while females managed and utilised their own emotions better. With female participants verbal aggression was higher, whereas males scored higher on physical aggression, anger aggression and hostile aggression. On the basis of location, urban adolescents were indicated to have the ability to perceive other's emotions and manage their own emotions, while rural adolescents results indicated a lesser propensity for the perception of others emotions and the management of own emotions. Both urban and rural adolescents indicated verbal aggression. Emotional intelligence and aggression vary with gender and location. Therefore, gender-specific characteristics, and location, could play a major role in how the behaviour is manifested. Based on these findings, it is concluded that intervention methods should be tailor-made to suit individual needs.
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The survival of enterprises and the effective management of daily problems and obstacles, particularly those faced by small entrepreneurs, depend heavily on resilience. This study examines the critical elements that help small Saudi entrepreneurs strengthen their entrepreneurial resilience through internal locus of control and entrepreneurial self-efficacy, particularly during trying times. The partial least squares structural equation modeling (PLS–SEM) technique was used to analyse the responses of 207 small entrepreneurs operating in various regions of Saudi Arabia. The convenience sampling technique was used, and the data was collected using an online questionnaire. The study found a strong relationship between entrepreneurial resilience, internal locus of control, and entrepreneurial self-efficacy. These results demonstrated that entrepreneurial self-efficacy could mediate the relationship between the internal locus of control and entrepreneurial resilience. Finally, the study addressed limitations and provided recommendations for policymakers and potential authors.
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The present study intends to investigate the influence of entrepreneurs' self-compassion (i.e., self-judgment, self-isolation, and mindfulness) on family-owned small business (F-OSB) performance during the pandemic. A conceptual model with self-judgment, self-isolation, mindfulness (formative constructs), and F-OSB performance (reflective construct) was based on three hypotheses. Primary data (n=227) was collected from entrepreneurs designated as CEO, Chairman, or managing directors in F-OSBs in Pakistan. The study used Partial Least Square Structural Equation Modelling (PLS-SEM) through Smart-PLS software version 3.3.2. First, the reliability and validity of the constructs were tested. In the next step bootstrapping to test the hypothesis was implemented. Self-control theory is used to explain the conceptual model. Results revealed that self-judgment and self-isolation have a significant negative while mindfulness has a significant positive association with F-OSB performance. The research contributed to literature and theory and has a post-pandemic practical contribution. First, the study filled a research gap by investigating the relationship between self-compassion and F-OSB performance. Second, this study contributed to the self-control theory by explaining the aforementioned relationship in the F-OSB context. Third, the results implied that, along with vaccination and financial support by the governments, F-OSB entrepreneurs must be provided psychological training sessions to cope with the negative effects of self-judgment and self-isolation due to lockdowns. Thus, F-OSB entrepreneurs not only perform well after COVID and become psychologically strong to take vigilant and calculated initiative for their businesses' and families' betterment.
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The practice course about electric motor controlling is essential in establishing undergraduate students' skills in many electronics and electrical engineering majors. However, due to the current COVID-19 situation, teaching this practical subject has become unlearnable in the laboratory room. Therefore, the urgent requirement is to find a solution to virtualize many electrical-motor control lessons for online learning during the distant social period. In this paper, we propose a potential solution to online practical electrical motor control coursework based on Proteus software. Unlike the common Matlab Simulink approach, the Proteus has the advantage of digitizing both the Arduino device and the electric circuits. We demonstrate the usefulness of Proteus 8.2 software by implementing a circuit to control a 3-phase asynchronous motor using the pulse width control method, named sine PWM. Through the learning on Proteus software, students not only review the theoretical knowledge of electrical motors but also learn how to apply the theory through simulating virtualized Arduino devices and building a control circuit with the control block to control the motor in real-Time. Furthermore, Proteus also supports printing out the control circuit board for the user. Proteus is, therefore, a suitable solution for online teaching of practice subjects for related majors. © 2022 IEEE.
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After the outbreak of COVID-19, the freight demand fell briefly, and as production resumed, the trucking share rate increased again, further increasing energy consumption and environmental pollution. To optimize the sudden changing freight structure, the study aims on developing an evolution model based on Markov's theory to estimate the freight structure post-COVID-19. The current study applies economic cybernetics to establish a freight structural adjustment path optimization model and solve the problem of how much freight transportation should increase each year under the premise that the total turnover of the freight industry continues to grow, and how many years it will take at least to reach a reasonable freight structure. The freight transport structure of China is used to examine the feasibility of the proposed model. The finding indicates that the development of China's freight transport structure is at an adjustment period and should enter a stable period by 2035 and the COVID-19 makes it harder to adjust the freight structure. Increasing the growth rate of the freight volume of railway and waterway transportation is the key to realizing the optimization of the freight structure, and the freight structure path optimization method can realize the rationalization of the freight structure in advance.
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In this article, we examine citizens' willingness to comply with Covid-19 prevention strategies of mandatory mask-wearing and recommended social distance/contact limitation measures from competing theoretical perspectives. These include self-control, deterrence, learning, social control theories, and fear of the infection. Data for the study come from 508 respondents from St. Petersburg—Russia's second largest city—in May 2020, when the Covid-19 regional legislation that mandated citizens to wear masks in public went into effect. Overall, our findings suggest mixed support for various theoretical perspectives. Among the variables included in the analysis, fear of the infection is positively related to compliance with both mandated and recommended measures. Fear of Covid-19 infection, fear of punishment, and fear of disapproval on behalf of significant others that would follow non-compliance appear to be strong predictors of law-abiding behavior. Learning and self-control theories explain compliance with non-mandatory measures, but not with mask-wearing, which carried a penalty for violating the mandate. [ FROM AUTHOR]
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COVID-19 pandemic is still a great challenge for several research fields. A mathematical model is one of the main epidemiology research contributions, which is able to study the pattern of disease spread and its long-term behavior. Many researchers have done this research with their interventions and mathematical approach methods, such as model analysis, use of optimal control theory, data used and numerical methods for solving the model. In this paper, we normalize the basic SIR epidemiological model and estimate the parameters involved based on the COVID-19 data in Indonesia, especially for West Java. The optimal control theory is applied to know the disease behavior by considering vaccination and its cost to prevent the spread of the disease. To see the disease behavior through graphical simulation, the Runge-Kutta Fehlberg method is used for solving the model numerically. The result shows that the spread of COVID-19 can be prevented and controlled due to vaccination. © 2022 the author(s).
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Dynamics in supply chains (SCs) can trigger risks due to the changing and propagating nature. In the context of COVID-19, this article presents an assessment-to-control decision-making support scheme to tackle propagation effect uncertainties of SCs considering product changes. First, a new decision model is proposed for risk warnings, with the potential advantages that: 1) propagation effects can be assessed generally and objectively and 2) permitting control theory to integrate and identify the interrelations between propagation effects. More specifically, the bullwhip effect (BE) with operational and behavioral causes is quantified as cascading amplified inventory fluctuations. The ripple effect (RE) from large-scale supplier disruptions driven by COVID-19 is quantified as increased entropy rates (ERs). Then, the system studied is integrated as a closed-loop control system under provided change control. Moreover, some criteria are derived for the existence of controller gains/decision coefficients to stabilize the closed-loop system with the BE mitigation under the RE. Finally, a mask SC case study under COVID-19 is performed for examining the effectiveness of the proposed scheme. IEEE