The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various ...The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives.The Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling problem.Nevertheless,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and diversity.To enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence issues.Furthermore,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex computation.To validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test instances.The experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.展开更多
The success of teachers in professional environments has a desirable influence on their mental condition.Simply said,teachers’professional success plays a crucial role in improving their mental health.Due to the inva...The success of teachers in professional environments has a desirable influence on their mental condition.Simply said,teachers’professional success plays a crucial role in improving their mental health.Due to the invaluable role of professional success in teachers’mental health,personal and professional variables helping teachers succeed in their profession need to be uncovered.While the role of teachers’personal qualities has been well researched,the function of professional variables has remained unknown.To address the existing gap,the current investigation measured the role of two professional variables,namely job satisfaction and loving pedagogy,in Chinese EFL teachers’professional success.To do this,three validated scales were provided to 1591 Chinese EFL teachers.Participants’answers to the questionnaires were analyzed using the Spearman correlation test and structural equation modeling.The data analysis demonstrated a strong,positive link between the variables.Moreover,loving pedagogy was found to be the positive,strong predictor of Chinese EFL teachers’job satisfaction and professional success.The findings of the current inquiry may help educational administrators enhance their instructors’professional success,which in turn promotes their mental and psychological conditions at work.展开更多
Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been...Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.展开更多
Evidence showed occupational factors may contribute distress to breast cancer survivors, however, very few studies focused on the occupational factors and job strain among breast cancer survivors. This study examined ...Evidence showed occupational factors may contribute distress to breast cancer survivors, however, very few studies focused on the occupational factors and job strain among breast cancer survivors. This study examined the relationship between job strain and workplace stressors with psychological distress among employed breast cancer survivors after the completion of their medical treatment. Study subject were outpatients of 2 hospitals and members of 4 breast cancer support groups. They were requested to fill up the Job Content Questionnaires (JCQ), the Hospital Anxiety and Depression Scale (HADS) and the Distress Thermometer (DT) were filled up by the selected respondents. On simple logistic regression, psychological job demand and job strain were significantly associated with anxiety, distress on HADS-T and DT at (p < 0.001). While, psychological job demand (p < 0.001), social support (p = 0.047) and job strain (p < 0.001) were significantly associated with depression. Results showed survivors with high job strain has 4.74 time the odds of having anxiety (p < 0.001). Survivors with high psychological job demand have 8.08 time the odds of getting depression (p < 0.001). On the other hand, social support served as a protective factor of depression, (p = 0.041). Survivors with high psychological job demand were 4.4 time the odds of having distress (HADS-T) (p = 0.012). As a conclusion, survivors who experienced high psychological job demand, low social support and high job strain were reported with anxiety, depression or psychological distress.展开更多
As a typical transportation tool in the intelligent manufacturing system,Automatic Guided Vehicle(AGV)plays an indispensable role in the automatic production process of the workshop.Therefore,integrating AGV resources...As a typical transportation tool in the intelligent manufacturing system,Automatic Guided Vehicle(AGV)plays an indispensable role in the automatic production process of the workshop.Therefore,integrating AGV resources into production scheduling has become a research hotspot.For the scheduling problem of the flexible job shop adopting segmented AGV,a dual-resource scheduling optimization mathematical model of machine tools and AGVs is established by minimizing the maximum completion time as the objective function,and an improved genetic algorithmis designed to solve the problem in this study.The algorithmdesigns a two-layer codingmethod based on process coding and machine tool coding and embeds the task allocation of AGV into the decoding process to realize the real dual resource integrated scheduling.When initializing the population,three strategies are designed to ensure the diversity of the population.In order to improve the local search ability and the quality of the solution of the genetic algorithm,three neighborhood structures are designed for variable neighborhood search.The superiority of the improved genetic algorithmand the influence of the location and number of transfer stations on scheduling results are verified in two cases.展开更多
Job shop scheduling(JS)is an important technology for modern manufacturing.Flexible job shop scheduling(FJS)is critical in JS,and it has been widely employed in many industries,including aerospace and energy.FJS enabl...Job shop scheduling(JS)is an important technology for modern manufacturing.Flexible job shop scheduling(FJS)is critical in JS,and it has been widely employed in many industries,including aerospace and energy.FJS enables any machine from a certain set to handle an operation,and this is an NP-hard problem.Furthermore,due to the requirements in real-world cases,multi-objective FJS is increasingly widespread,thus increasing the challenge of solving the FJS problems.As a result,it is necessary to develop a novel method to address this challenge.To achieve this goal,a novel collaborative evolutionary algorithmwith two-population based on Pareto optimality is proposed for FJS,which improves the solutions of FJS by interacting in each generation.In addition,several experimental results have demonstrated that the proposed method is promising and effective for multi-objective FJS,which has discovered some new Pareto solutions in the well-known benchmark problems,and some solutions can dominate the solutions of some other methods.展开更多
<strong>Objective: </strong>With the development of society, people’s requirements and standards for nursing work continue to improve, under the premise of nursing human resources are relatively insuffici...<strong>Objective: </strong>With the development of society, people’s requirements and standards for nursing work continue to improve, under the premise of nursing human resources are relatively insufficient, nursing work from nursing skills to service attitude to ensure quality, this standard brings great work pressure to nursing staff, in addition, the increasing medical disputes, It increases the risk factor of personal safety attack in the workplace of nurses, and further increases the psychological pressure of nurses, thus increasing the incidence of job burnout of nurses. <strong>Methods: </strong>A multi-stage random sampling was adopted to conduct a questionnaire survey among 1049 nursing staff on December 1, solstice and December 30, 2015. The current situation of nurses’ job satisfaction, stressors and job burnout and its influencing factors were analyzed. <strong>Results: </strong>1) The total score of nurses’ job satisfaction was 91.52 ± 17.99 points;2) The total score of nurses’ work stressors was 86.52 ± 21.95 points;3) The total score of nurses’ job burnout was 38.44 ± 7.55 points;4) The aspects of patient care, management and interpersonal relationship were significantly correlated with nurses’ burnout (P < 0.001), and the total score of job satisfaction was positively correlated with nurses’ burnout, while the total score of job satisfaction was negatively correlated with nurses’ burnout. There was a significant correlation between job title and nurse burnout (P < 0.001). <strong>Conclusion:</strong> The job burnout of nurses is related to nurse satisfaction and work pressure. The problems of management and interpersonal relationship, title, total score of job satisfaction and patient care are the main problems of nurses’ job burnout.展开更多
Background: The COVID-19 outbreak negatively impacted pharmacists who provided basic medical services by inducing anxiety and depression, thus, leading to medical errors. Objective: This study aimed to investigate the...Background: The COVID-19 outbreak negatively impacted pharmacists who provided basic medical services by inducing anxiety and depression, thus, leading to medical errors. Objective: This study aimed to investigate the job burnout and satisfaction levels among hospital pharmacists during the period when China downgraded COVID-19 from a Category A disease to a Category B disease. Method: We selected pharmacists from several medical institutions in Yunnan Province as the subjects by using the general information questionnaire survey, the Maslach Burnout Inventory-Human Services Survey (MBI-HSS), and the Work Environment Scale-10 (WES-10). Results: After analyzing 461 questionnaires, the results showed that the age and marital status of the pharmacists displayed significant effects on their emotional exhaustion and sense of achievement, with younger pharmacists getting higher and lower scores for their tests on emotional exhaustion and sense of achievement, respectively (p Conclusion: Hence, it was concluded that the job burnout of pharmacists was at a low level during the period when China downgraded COVID-19 as a Category B disease from Category A.展开更多
The job shop scheduling problem(JSSP)is a classical combinatorial optimization problem that exists widely in diverse scenarios of manufacturing systems.It is a well-known NP-hard problem,when the number of jobs increa...The job shop scheduling problem(JSSP)is a classical combinatorial optimization problem that exists widely in diverse scenarios of manufacturing systems.It is a well-known NP-hard problem,when the number of jobs increases,the difficulty of solving the problem exponentially increases.Therefore,a major challenge is to increase the solving efficiency of current algorithms.Modifying the neighborhood structure of the solutions can effectively improve the local search ability and efficiency.In this paper,a genetic Tabu search algorithm with neighborhood clipping(GTS_NC)is proposed for solving JSSP.A neighborhood solution clipping method is developed and embedded into Tabu search to improve the efficiency of the local search by clipping the search actions of unimproved neighborhood solutions.Moreover,a feasible neighborhood solution determination method is put forward,which can accurately distinguish feasible neighborhood solutions from infeasible ones.Both of the methods are based on the domain knowledge of JSSP.The proposed algorithmis compared with several competitive algorithms on benchmark instances.The experimental results show that the proposed algorithm can achieve superior results compared to other competitive algorithms.According to the numerical results of the experiments,it is verified that the neighborhood solution clippingmethod can accurately identify the unimproved solutions and reduces the computational time by at least 28%.展开更多
Background: Mental health has been impaired and at risk due to the worldwide COVID-19 pandemic. The consequences due to confinement impacted every scenario, which directly influenced the daily routine of nurse student...Background: Mental health has been impaired and at risk due to the worldwide COVID-19 pandemic. The consequences due to confinement impacted every scenario, which directly influenced the daily routine of nurse students;in each setting students faced stressors that trigger fear, anxiety and others, since being in confinement learning of topics moved to the home, laboratory practices in hospitals were cancelled leaving the room that is uncertain up to their return to in-person activities. It is important to highlight the need for innovation and strengthening of theoretical-pedagogic aspects centered at the student’s context as a human being with their own needs and problems, who will interact with others in the continuous process of health-illness. Objective: the aim was to identify the stressors in the nurse students’ formation in the new normality post-COVID-19. Methods: Qualitative and phenomenological research with 27 participants aged 20 - 25 years, nurse students of a public university. The information collection was through four focal groups of 6-7 members each, data analysis was done according to Miles & Huberman after signed informed consent of each participant, and authorized by the chairperson of the Nurse’ career. Results: Category 1, Cumulative stressors with sub-categories 1.1 Uncertainty, 1.2 Isolation, 1.3 Invisibility, 1.4 Mockery, 1.5 Exclusion. Category 2, Expectancy states with sub-categories 2.1 Low self-esteem, 2.2 Insecurity, 2.3 Anxiety, 2.4 Depression, 2.5 Temporary leave, 2.6 Search for authenticity. Category 3, Internalization processes with sub-categories 3.1 Social rejection, 3.2 Self-censorship, 3.3 Discrediting, 3.4 Disempowerment. Category 4, Academic aspects affected with sub-categories 4.1 Deficient studying habits, 4.2 Deficient assimilations of knowledge, 4.3 Archived knowledge in the computer, 4.4 Absence of practice in previous semesters. Conclusion: Once identified the stressors in nurse students in the new normality post-COVID-19, it will allow the creation of settings that help in getting confidence for students, i.e., a safe surrounding promotes the development of abilities and competencies during formation, as well as recommendations of teachers in the classroom and laboratories that contribute to filling space that students perceive as empty, and to intensifying the companionship in clinical settings where students perceive most aggressiveness.展开更多
Introduction: Nurses’ job satisfaction is referring to the level to which people feel that they are able to have an influence on their workplace. Nurse leaders should use a variety of empowerment strategies that are ...Introduction: Nurses’ job satisfaction is referring to the level to which people feel that they are able to have an influence on their workplace. Nurse leaders should use a variety of empowerment strategies that are important to nurses’ job satisfaction. Meanwhile, meaningful recognition for nurses is considered a powerful tool to enhance nurses’ sense of self-efficacy especially facing an emotional challenge that may affect their wellbeing. Aim: The aim of the studies is to analyze the importance of nurses’ recognition, and empowerment towards nurses’ job satisfaction at KFSH-D. Method: This study takes the form of a quantitative research methodology, and descriptive-analytical technique. A questionnaire used to gather data from registered nurses employed at King Fahad Specialist Hospital-Dammam (KFSH-D) about the structural empowerment and nurses’ recognition program impact on their job satisfaction. Following the collection of data, the descriptive statistic used to describe the personal characteristics of the respondents, while inferential statistics used to determine the statistical relationship existing between independent variable job satisfaction and the structural empowerment and nurses’ recognition program among the registered nurses at KFSH-D as dependent variables. Recommendation: The researcher only focuses on the in-patient units, future studies, are recommended to focus on every dimension and category level of units. Apart from that, when looking into job satisfaction and empowerment, to be more specific, the researcher could investigate another dimension by comparing age, and clinical working experience which may provide a depth of understanding of the contribution perception of structural empowerment. Conclusion: The findings of the studies reveal recognition and empowerment are assets to make nurses stay and increase their level of job satisfaction and task assignments.展开更多
Nowadays, in data science, supervised learning algorithms are frequently used to perform text classification. However, African textual data, in general, have been studied very little using these methods. This article ...Nowadays, in data science, supervised learning algorithms are frequently used to perform text classification. However, African textual data, in general, have been studied very little using these methods. This article notes the particularity of the data and measures the level of precision of predictions of naive Bayes algorithms, decision tree, and SVM (Support Vector Machine) on a corpus of computer jobs taken on the internet. This is due to the data imbalance problem in machine learning. However, this problem essentially focuses on the distribution of the number of documents in each class or subclass. Here, we delve deeper into the problem to the word count distribution in a set of documents. The results are compared with those obtained on a set of French IT offers. It appears that the precision of the classification varies between 88% and 90% for French offers against 67%, at most, for Cameroonian offers. The contribution of this study is twofold. Indeed, it clearly shows that, in a similar job category, job offers on the internet in Cameroon are more unstructured compared to those available in France, for example. Moreover, it makes it possible to emit a strong hypothesis according to which sets of texts having a symmetrical distribution of the number of words obtain better results with supervised learning algorithms.展开更多
There are a plethora of empirical pieces about employees’pro-environmental behaviors.However,the extant literature has either ignored or not fully examined various factors(e.g.,negative or positive non-green workplac...There are a plethora of empirical pieces about employees’pro-environmental behaviors.However,the extant literature has either ignored or not fully examined various factors(e.g.,negative or positive non-green workplace factors)that might affect employees’pro-environmental behaviors.Realizing these voids,the present paper proposes and tests a serial mediation model that examines the interrelationships of job insecurity,emotional exhaustion,met expectations,and proactive pro-environmental behavior.We used data gathered from hotel customer-contact employees with a time lag of one week and their direct supervisors in China.After presenting support for the psychometric properties of the measures via confirmatory analysis in LISREL 8.30,the abovementioned linkages were gauged using the PROCESS plug-in for statistical package for social sciences.The findings delineated support for the hypothesized associations.Specifically,emotional exhaustion and met expectations partly mediated the effect of job insecurity on proactive pro-environmental behavior.More importantly,emotional exhaustion and met expectations serially mediated the influence of job insecurity on proactive pro-environmental behavior.These findings have important theoretical implications as well as significant implications for diminishing job insecurity,managing emotional exhaustion,increasing met expectations,and enhancing ecofriendly behaviors.展开更多
Big data analytics in business intelligence do not provide effective data retrieval methods and job scheduling that will cause execution inefficiency and low system throughput.This paper aims to enhance the capability...Big data analytics in business intelligence do not provide effective data retrieval methods and job scheduling that will cause execution inefficiency and low system throughput.This paper aims to enhance the capability of data retrieval and job scheduling to speed up the operation of big data analytics to overcome inefficiency and low throughput problems.First,integrating stacked sparse autoencoder and Elasticsearch indexing explored fast data searching and distributed indexing,which reduces the search scope of the database and dramatically speeds up data searching.Next,exploiting a deep neural network to predict the approximate execution time of a job gives prioritized job scheduling based on the shortest job first,which reduces the average waiting time of job execution.As a result,the proposed data retrieval approach outperforms the previous method using a deep autoencoder and Solr indexing,significantly improving the speed of data retrieval up to 53%and increasing system throughput by 53%.On the other hand,the proposed job scheduling algorithmdefeats both first-in-first-out andmemory-sensitive heterogeneous early finish time scheduling algorithms,effectively shortening the average waiting time up to 5%and average weighted turnaround time by 19%,respectively.展开更多
A condition of exposure to multiple stressors resulting in a mixed clinical picture spanning conventional categories without meeting any of them in full,encompasses a risk for a list of comorbidities preventing approp...A condition of exposure to multiple stressors resulting in a mixed clinical picture spanning conventional categories without meeting any of them in full,encompasses a risk for a list of comorbidities preventing appropriate prevention and treatment.New transformative transdiagnostic approaches suggest changes spanning conventional categories.They base their systems of classification on biomarkers as well as on brain structural and functional dysregulation as associated with behavioral and emotional symptoms.These new approaches received critiques for not being specific enough and for suggesting a few biomarkers for psychopathology as a whole.Therefore,they put the value of differential diagnosis at risk of avoiding appropriate derived prevention and treatment.Multiplicity of stressors has been considered mostly during and following catastrophes,without considering the resulting mixed clinical picture and life event concomitant stressors.We herewith suggest a new category within the conventional classification systems:The Complex Stress Reaction Syndrome,for a condition of multiplicity of stressors,which showed a mixed clinical picture for daily life in the post coronavirus disease 2019 era,in the general population.We argue that this condition may be relevant to daily,regular life,across the lifespan,and beyond conditions of catastrophes.We further argue that this condition may worsen without professional care and it may develop into a severe mental health disorder,more costly to health systems and the suffering individuals.Means for derived prevention and treatment are discussed.展开更多
Objective:The objective of the present study is to explore the effects of personality traits on job burnout among hospital nurses.Materials and Methods:This cross-sectional research was done during 2019-2020 at Kashan...Objective:The objective of the present study is to explore the effects of personality traits on job burnout among hospital nurses.Materials and Methods:This cross-sectional research was done during 2019-2020 at Kashan Shahid Beheshti Hospital.The data analysis procedures included descriptive statistics and the partial least squares-based structural equation modeling.The participants were 150 nursing professionals.A questionnaire indicating information on demographics,burnout(measured using the Maslach Burnout Inventory with three dimensions of depersonalization,emotional exhaustion,and personal accomplishment),and personality profile(measured employing the neuroticism extraversion openness five-factor inventory including extroversion,conscientiousness,agreeableness,neuroticism,and openness to experience dimensions)was used to gather the required data.Results:The results of the study showed that the validity and reliability of the measurement model were desirable(factor load higher than 0.5,the Cronbach’s alpha value and the composite reliability are>0.7).Structural model showed statistically drastic,negative relationship between the nurses’burnout levels and neuroticism(β=0.722)and openness to experience(β=0.437).However,the relationship was significantly positive between the nurses’burnout levels and conscientiousness(β=0.672),agreement(β=0.594),and extraversion(β=0.559)(P<0.03).Conclusions:The present study helped the recognition of burnout among nurses working in hospitals and approved the effects of personality features on the burnout experience.展开更多
A small and medium enterprises(SMEs)manufacturing platform aims to perform as a significant revenue to SMEs and vendors by providing scheduling and monitoring capabilities.The optimal job shop scheduling is generated ...A small and medium enterprises(SMEs)manufacturing platform aims to perform as a significant revenue to SMEs and vendors by providing scheduling and monitoring capabilities.The optimal job shop scheduling is generated by utilizing the scheduling system of the platform,and a minimum production time,i.e.,makespan decides whether the scheduling is optimal or not.This scheduling result allows manufacturers to achieve high productivity,energy savings,and customer satisfaction.Manufacturing in Industry 4.0 requires dynamic,uncertain,complex production environments,and customer-centered services.This paper proposes a novel method for solving the difficulties of the SMEs manufacturing by applying and implementing the job shop scheduling system on a SMEs manufacturing platform.The primary purpose of the SMEs manufacturing platform is to improve the B2B relationship between manufacturing companies and vendors.The platform also serves qualified and satisfactory production opportunities for buyers and producers by meeting two key factors:early delivery date and fulfillment of processing as many orders as possible.The genetic algorithm(GA)-based scheduling method results indicated that the proposed platform enables SME manufacturers to obtain optimized schedules by solving the job shop scheduling problem(JSSP)by comparing with the real-world data from a textile weaving factory in South Korea.The proposed platform will provide producers with an optimal production schedule,introduce new producers to buyers,and eventually foster relationships and mutual economic interests.展开更多
Objective:To investigate the factors contributing to satisfaction with the work environment,job satisfaction(JS),and stress among hemodialysis(HD)staff in the central region of Malaysia.Methods:A quantitative cross-se...Objective:To investigate the factors contributing to satisfaction with the work environment,job satisfaction(JS),and stress among hemodialysis(HD)staff in the central region of Malaysia.Methods:A quantitative cross-sectional study was conducted on 215 HD staff working at private and non-government(NGO)dialysis centers using self-administered questionnaires.The chi-square test was used to determine factors associated with HD staff's JS,stress,and working environment.Results:The scientific proof was apparent that the working environment had an effect on JS and stress among employees at HD centers.Conclusions:This research offers useful insights into the essence and complexities of HD staff's work and will help nurses,dialysis managers,other dialysis personnel,and organizations to better understand the benefits and stresses faced by these workers.展开更多
The Big Five Theory is often regarded as psychology’s most influential personality theoretical approach.The goal of this study is to examine the role of the Big Five Theory in the workplace,especially which personali...The Big Five Theory is often regarded as psychology’s most influential personality theoretical approach.The goal of this study is to examine the role of the Big Five Theory in the workplace,especially which personality qualities are more likely to predict work success.Which traits should companies emphasize throughout the hiring and selection processes?How can businesses use the Big Five personality model to locate employees that are more productive,efficient,and devoted to the organization’s goals?A detailed assessment of existing recent research addresses the aforementioned issues.Following a review of many current articles on the subject,it was established that using this model had a positive influence on individual and group performance,working relationships,manager work performance,and workplace innovation.展开更多
Saul Bellow’s novel Seize the Day combines the psychological narrative of Jewish immigrants in the“Happy Age”of the United States and the daily life narrative of modern New York urbanites,revealing the living state...Saul Bellow’s novel Seize the Day combines the psychological narrative of Jewish immigrants in the“Happy Age”of the United States and the daily life narrative of modern New York urbanites,revealing the living state of modern urbanites-powerless to the outside world,nowhere to live in the material and spiritual world.They have an unresolved personal pursuit and a“dangling”destiny,which alludes to the problems plaguing modern urban people and the decay of American society.By comparing the characteristics and fate of the protagonist Wilhelm with the character Job in the Bible,this article helps to deepen the understanding of the plights of the protagonist as“Modern Job”,and realize the influence of the American urban society on Jewishness and personal survival in that period.展开更多
基金in part supported by the Key Research and Development Project of Hubei Province(Nos.2020BAB1141,2023BAB094)the Key Project of Science and Technology Research ProgramofHubei Educational Committee(No.D20211402)+1 种基金the Teaching Research Project of Hubei University of Technology(No.XIAO2018001)the Project of Xiangyang Industrial Research Institute of Hubei University of Technology(No.XYYJ2022C04).
文摘The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives.The Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling problem.Nevertheless,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and diversity.To enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence issues.Furthermore,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex computation.To validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test instances.The experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.
基金sponsored by the Research Project of Jiangsu Social Science Fund Project,entitled“Research on Irrational Expression of Crisis Discourse”(Grant No.21YYD001)Basic Foreign Language Education Research Project of Changshu Institute of Technology,entitled“A Study on the Regulation Mechanism of Professional Happiness of Foreign Language Teachers in Primary and Secondary Schools from the Perspective of Positive Psychology”(Grant No.2022cslgwgy008).
文摘The success of teachers in professional environments has a desirable influence on their mental condition.Simply said,teachers’professional success plays a crucial role in improving their mental health.Due to the invaluable role of professional success in teachers’mental health,personal and professional variables helping teachers succeed in their profession need to be uncovered.While the role of teachers’personal qualities has been well researched,the function of professional variables has remained unknown.To address the existing gap,the current investigation measured the role of two professional variables,namely job satisfaction and loving pedagogy,in Chinese EFL teachers’professional success.To do this,three validated scales were provided to 1591 Chinese EFL teachers.Participants’answers to the questionnaires were analyzed using the Spearman correlation test and structural equation modeling.The data analysis demonstrated a strong,positive link between the variables.Moreover,loving pedagogy was found to be the positive,strong predictor of Chinese EFL teachers’job satisfaction and professional success.The findings of the current inquiry may help educational administrators enhance their instructors’professional success,which in turn promotes their mental and psychological conditions at work.
文摘Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.
文摘Evidence showed occupational factors may contribute distress to breast cancer survivors, however, very few studies focused on the occupational factors and job strain among breast cancer survivors. This study examined the relationship between job strain and workplace stressors with psychological distress among employed breast cancer survivors after the completion of their medical treatment. Study subject were outpatients of 2 hospitals and members of 4 breast cancer support groups. They were requested to fill up the Job Content Questionnaires (JCQ), the Hospital Anxiety and Depression Scale (HADS) and the Distress Thermometer (DT) were filled up by the selected respondents. On simple logistic regression, psychological job demand and job strain were significantly associated with anxiety, distress on HADS-T and DT at (p < 0.001). While, psychological job demand (p < 0.001), social support (p = 0.047) and job strain (p < 0.001) were significantly associated with depression. Results showed survivors with high job strain has 4.74 time the odds of having anxiety (p < 0.001). Survivors with high psychological job demand have 8.08 time the odds of getting depression (p < 0.001). On the other hand, social support served as a protective factor of depression, (p = 0.041). Survivors with high psychological job demand were 4.4 time the odds of having distress (HADS-T) (p = 0.012). As a conclusion, survivors who experienced high psychological job demand, low social support and high job strain were reported with anxiety, depression or psychological distress.
文摘As a typical transportation tool in the intelligent manufacturing system,Automatic Guided Vehicle(AGV)plays an indispensable role in the automatic production process of the workshop.Therefore,integrating AGV resources into production scheduling has become a research hotspot.For the scheduling problem of the flexible job shop adopting segmented AGV,a dual-resource scheduling optimization mathematical model of machine tools and AGVs is established by minimizing the maximum completion time as the objective function,and an improved genetic algorithmis designed to solve the problem in this study.The algorithmdesigns a two-layer codingmethod based on process coding and machine tool coding and embeds the task allocation of AGV into the decoding process to realize the real dual resource integrated scheduling.When initializing the population,three strategies are designed to ensure the diversity of the population.In order to improve the local search ability and the quality of the solution of the genetic algorithm,three neighborhood structures are designed for variable neighborhood search.The superiority of the improved genetic algorithmand the influence of the location and number of transfer stations on scheduling results are verified in two cases.
基金This research work is the Key R&D Program of Hubei Province under Grant No.2021AAB001National Natural Science Foundation of China under Grant No.U21B2029。
文摘Job shop scheduling(JS)is an important technology for modern manufacturing.Flexible job shop scheduling(FJS)is critical in JS,and it has been widely employed in many industries,including aerospace and energy.FJS enables any machine from a certain set to handle an operation,and this is an NP-hard problem.Furthermore,due to the requirements in real-world cases,multi-objective FJS is increasingly widespread,thus increasing the challenge of solving the FJS problems.As a result,it is necessary to develop a novel method to address this challenge.To achieve this goal,a novel collaborative evolutionary algorithmwith two-population based on Pareto optimality is proposed for FJS,which improves the solutions of FJS by interacting in each generation.In addition,several experimental results have demonstrated that the proposed method is promising and effective for multi-objective FJS,which has discovered some new Pareto solutions in the well-known benchmark problems,and some solutions can dominate the solutions of some other methods.
文摘<strong>Objective: </strong>With the development of society, people’s requirements and standards for nursing work continue to improve, under the premise of nursing human resources are relatively insufficient, nursing work from nursing skills to service attitude to ensure quality, this standard brings great work pressure to nursing staff, in addition, the increasing medical disputes, It increases the risk factor of personal safety attack in the workplace of nurses, and further increases the psychological pressure of nurses, thus increasing the incidence of job burnout of nurses. <strong>Methods: </strong>A multi-stage random sampling was adopted to conduct a questionnaire survey among 1049 nursing staff on December 1, solstice and December 30, 2015. The current situation of nurses’ job satisfaction, stressors and job burnout and its influencing factors were analyzed. <strong>Results: </strong>1) The total score of nurses’ job satisfaction was 91.52 ± 17.99 points;2) The total score of nurses’ work stressors was 86.52 ± 21.95 points;3) The total score of nurses’ job burnout was 38.44 ± 7.55 points;4) The aspects of patient care, management and interpersonal relationship were significantly correlated with nurses’ burnout (P < 0.001), and the total score of job satisfaction was positively correlated with nurses’ burnout, while the total score of job satisfaction was negatively correlated with nurses’ burnout. There was a significant correlation between job title and nurse burnout (P < 0.001). <strong>Conclusion:</strong> The job burnout of nurses is related to nurse satisfaction and work pressure. The problems of management and interpersonal relationship, title, total score of job satisfaction and patient care are the main problems of nurses’ job burnout.
文摘Background: The COVID-19 outbreak negatively impacted pharmacists who provided basic medical services by inducing anxiety and depression, thus, leading to medical errors. Objective: This study aimed to investigate the job burnout and satisfaction levels among hospital pharmacists during the period when China downgraded COVID-19 from a Category A disease to a Category B disease. Method: We selected pharmacists from several medical institutions in Yunnan Province as the subjects by using the general information questionnaire survey, the Maslach Burnout Inventory-Human Services Survey (MBI-HSS), and the Work Environment Scale-10 (WES-10). Results: After analyzing 461 questionnaires, the results showed that the age and marital status of the pharmacists displayed significant effects on their emotional exhaustion and sense of achievement, with younger pharmacists getting higher and lower scores for their tests on emotional exhaustion and sense of achievement, respectively (p Conclusion: Hence, it was concluded that the job burnout of pharmacists was at a low level during the period when China downgraded COVID-19 as a Category B disease from Category A.
基金supported byNationalNatural Science Foundation forDistinguished Young Scholars of China(under the Grant No.51825502).
文摘The job shop scheduling problem(JSSP)is a classical combinatorial optimization problem that exists widely in diverse scenarios of manufacturing systems.It is a well-known NP-hard problem,when the number of jobs increases,the difficulty of solving the problem exponentially increases.Therefore,a major challenge is to increase the solving efficiency of current algorithms.Modifying the neighborhood structure of the solutions can effectively improve the local search ability and efficiency.In this paper,a genetic Tabu search algorithm with neighborhood clipping(GTS_NC)is proposed for solving JSSP.A neighborhood solution clipping method is developed and embedded into Tabu search to improve the efficiency of the local search by clipping the search actions of unimproved neighborhood solutions.Moreover,a feasible neighborhood solution determination method is put forward,which can accurately distinguish feasible neighborhood solutions from infeasible ones.Both of the methods are based on the domain knowledge of JSSP.The proposed algorithmis compared with several competitive algorithms on benchmark instances.The experimental results show that the proposed algorithm can achieve superior results compared to other competitive algorithms.According to the numerical results of the experiments,it is verified that the neighborhood solution clippingmethod can accurately identify the unimproved solutions and reduces the computational time by at least 28%.
文摘Background: Mental health has been impaired and at risk due to the worldwide COVID-19 pandemic. The consequences due to confinement impacted every scenario, which directly influenced the daily routine of nurse students;in each setting students faced stressors that trigger fear, anxiety and others, since being in confinement learning of topics moved to the home, laboratory practices in hospitals were cancelled leaving the room that is uncertain up to their return to in-person activities. It is important to highlight the need for innovation and strengthening of theoretical-pedagogic aspects centered at the student’s context as a human being with their own needs and problems, who will interact with others in the continuous process of health-illness. Objective: the aim was to identify the stressors in the nurse students’ formation in the new normality post-COVID-19. Methods: Qualitative and phenomenological research with 27 participants aged 20 - 25 years, nurse students of a public university. The information collection was through four focal groups of 6-7 members each, data analysis was done according to Miles & Huberman after signed informed consent of each participant, and authorized by the chairperson of the Nurse’ career. Results: Category 1, Cumulative stressors with sub-categories 1.1 Uncertainty, 1.2 Isolation, 1.3 Invisibility, 1.4 Mockery, 1.5 Exclusion. Category 2, Expectancy states with sub-categories 2.1 Low self-esteem, 2.2 Insecurity, 2.3 Anxiety, 2.4 Depression, 2.5 Temporary leave, 2.6 Search for authenticity. Category 3, Internalization processes with sub-categories 3.1 Social rejection, 3.2 Self-censorship, 3.3 Discrediting, 3.4 Disempowerment. Category 4, Academic aspects affected with sub-categories 4.1 Deficient studying habits, 4.2 Deficient assimilations of knowledge, 4.3 Archived knowledge in the computer, 4.4 Absence of practice in previous semesters. Conclusion: Once identified the stressors in nurse students in the new normality post-COVID-19, it will allow the creation of settings that help in getting confidence for students, i.e., a safe surrounding promotes the development of abilities and competencies during formation, as well as recommendations of teachers in the classroom and laboratories that contribute to filling space that students perceive as empty, and to intensifying the companionship in clinical settings where students perceive most aggressiveness.
文摘Introduction: Nurses’ job satisfaction is referring to the level to which people feel that they are able to have an influence on their workplace. Nurse leaders should use a variety of empowerment strategies that are important to nurses’ job satisfaction. Meanwhile, meaningful recognition for nurses is considered a powerful tool to enhance nurses’ sense of self-efficacy especially facing an emotional challenge that may affect their wellbeing. Aim: The aim of the studies is to analyze the importance of nurses’ recognition, and empowerment towards nurses’ job satisfaction at KFSH-D. Method: This study takes the form of a quantitative research methodology, and descriptive-analytical technique. A questionnaire used to gather data from registered nurses employed at King Fahad Specialist Hospital-Dammam (KFSH-D) about the structural empowerment and nurses’ recognition program impact on their job satisfaction. Following the collection of data, the descriptive statistic used to describe the personal characteristics of the respondents, while inferential statistics used to determine the statistical relationship existing between independent variable job satisfaction and the structural empowerment and nurses’ recognition program among the registered nurses at KFSH-D as dependent variables. Recommendation: The researcher only focuses on the in-patient units, future studies, are recommended to focus on every dimension and category level of units. Apart from that, when looking into job satisfaction and empowerment, to be more specific, the researcher could investigate another dimension by comparing age, and clinical working experience which may provide a depth of understanding of the contribution perception of structural empowerment. Conclusion: The findings of the studies reveal recognition and empowerment are assets to make nurses stay and increase their level of job satisfaction and task assignments.
文摘Nowadays, in data science, supervised learning algorithms are frequently used to perform text classification. However, African textual data, in general, have been studied very little using these methods. This article notes the particularity of the data and measures the level of precision of predictions of naive Bayes algorithms, decision tree, and SVM (Support Vector Machine) on a corpus of computer jobs taken on the internet. This is due to the data imbalance problem in machine learning. However, this problem essentially focuses on the distribution of the number of documents in each class or subclass. Here, we delve deeper into the problem to the word count distribution in a set of documents. The results are compared with those obtained on a set of French IT offers. It appears that the precision of the classification varies between 88% and 90% for French offers against 67%, at most, for Cameroonian offers. The contribution of this study is twofold. Indeed, it clearly shows that, in a similar job category, job offers on the internet in Cameroon are more unstructured compared to those available in France, for example. Moreover, it makes it possible to emit a strong hypothesis according to which sets of texts having a symmetrical distribution of the number of words obtain better results with supervised learning algorithms.
文摘There are a plethora of empirical pieces about employees’pro-environmental behaviors.However,the extant literature has either ignored or not fully examined various factors(e.g.,negative or positive non-green workplace factors)that might affect employees’pro-environmental behaviors.Realizing these voids,the present paper proposes and tests a serial mediation model that examines the interrelationships of job insecurity,emotional exhaustion,met expectations,and proactive pro-environmental behavior.We used data gathered from hotel customer-contact employees with a time lag of one week and their direct supervisors in China.After presenting support for the psychometric properties of the measures via confirmatory analysis in LISREL 8.30,the abovementioned linkages were gauged using the PROCESS plug-in for statistical package for social sciences.The findings delineated support for the hypothesized associations.Specifically,emotional exhaustion and met expectations partly mediated the effect of job insecurity on proactive pro-environmental behavior.More importantly,emotional exhaustion and met expectations serially mediated the influence of job insecurity on proactive pro-environmental behavior.These findings have important theoretical implications as well as significant implications for diminishing job insecurity,managing emotional exhaustion,increasing met expectations,and enhancing ecofriendly behaviors.
基金supported and granted by the Ministry of Science and Technology,Taiwan(MOST110-2622-E-390-001 and MOST109-2622-E-390-002-CC3).
文摘Big data analytics in business intelligence do not provide effective data retrieval methods and job scheduling that will cause execution inefficiency and low system throughput.This paper aims to enhance the capability of data retrieval and job scheduling to speed up the operation of big data analytics to overcome inefficiency and low throughput problems.First,integrating stacked sparse autoencoder and Elasticsearch indexing explored fast data searching and distributed indexing,which reduces the search scope of the database and dramatically speeds up data searching.Next,exploiting a deep neural network to predict the approximate execution time of a job gives prioritized job scheduling based on the shortest job first,which reduces the average waiting time of job execution.As a result,the proposed data retrieval approach outperforms the previous method using a deep autoencoder and Solr indexing,significantly improving the speed of data retrieval up to 53%and increasing system throughput by 53%.On the other hand,the proposed job scheduling algorithmdefeats both first-in-first-out andmemory-sensitive heterogeneous early finish time scheduling algorithms,effectively shortening the average waiting time up to 5%and average weighted turnaround time by 19%,respectively.
文摘A condition of exposure to multiple stressors resulting in a mixed clinical picture spanning conventional categories without meeting any of them in full,encompasses a risk for a list of comorbidities preventing appropriate prevention and treatment.New transformative transdiagnostic approaches suggest changes spanning conventional categories.They base their systems of classification on biomarkers as well as on brain structural and functional dysregulation as associated with behavioral and emotional symptoms.These new approaches received critiques for not being specific enough and for suggesting a few biomarkers for psychopathology as a whole.Therefore,they put the value of differential diagnosis at risk of avoiding appropriate derived prevention and treatment.Multiplicity of stressors has been considered mostly during and following catastrophes,without considering the resulting mixed clinical picture and life event concomitant stressors.We herewith suggest a new category within the conventional classification systems:The Complex Stress Reaction Syndrome,for a condition of multiplicity of stressors,which showed a mixed clinical picture for daily life in the post coronavirus disease 2019 era,in the general population.We argue that this condition may be relevant to daily,regular life,across the lifespan,and beyond conditions of catastrophes.We further argue that this condition may worsen without professional care and it may develop into a severe mental health disorder,more costly to health systems and the suffering individuals.Means for derived prevention and treatment are discussed.
基金the Vice Chancellor of Research and Technology Kashan University of Medical Sciences for providing financial support to conduct this work(Approval code:94070).
文摘Objective:The objective of the present study is to explore the effects of personality traits on job burnout among hospital nurses.Materials and Methods:This cross-sectional research was done during 2019-2020 at Kashan Shahid Beheshti Hospital.The data analysis procedures included descriptive statistics and the partial least squares-based structural equation modeling.The participants were 150 nursing professionals.A questionnaire indicating information on demographics,burnout(measured using the Maslach Burnout Inventory with three dimensions of depersonalization,emotional exhaustion,and personal accomplishment),and personality profile(measured employing the neuroticism extraversion openness five-factor inventory including extroversion,conscientiousness,agreeableness,neuroticism,and openness to experience dimensions)was used to gather the required data.Results:The results of the study showed that the validity and reliability of the measurement model were desirable(factor load higher than 0.5,the Cronbach’s alpha value and the composite reliability are>0.7).Structural model showed statistically drastic,negative relationship between the nurses’burnout levels and neuroticism(β=0.722)and openness to experience(β=0.437).However,the relationship was significantly positive between the nurses’burnout levels and conscientiousness(β=0.672),agreement(β=0.594),and extraversion(β=0.559)(P<0.03).Conclusions:The present study helped the recognition of burnout among nurses working in hospitals and approved the effects of personality features on the burnout experience.
基金This work was supported by the Technology Innovation Program 20004205(the development of smart collaboration manufacturing innovation service platform in the textile industry by producer-buyer)funded by MOTIE,Korea.
文摘A small and medium enterprises(SMEs)manufacturing platform aims to perform as a significant revenue to SMEs and vendors by providing scheduling and monitoring capabilities.The optimal job shop scheduling is generated by utilizing the scheduling system of the platform,and a minimum production time,i.e.,makespan decides whether the scheduling is optimal or not.This scheduling result allows manufacturers to achieve high productivity,energy savings,and customer satisfaction.Manufacturing in Industry 4.0 requires dynamic,uncertain,complex production environments,and customer-centered services.This paper proposes a novel method for solving the difficulties of the SMEs manufacturing by applying and implementing the job shop scheduling system on a SMEs manufacturing platform.The primary purpose of the SMEs manufacturing platform is to improve the B2B relationship between manufacturing companies and vendors.The platform also serves qualified and satisfactory production opportunities for buyers and producers by meeting two key factors:early delivery date and fulfillment of processing as many orders as possible.The genetic algorithm(GA)-based scheduling method results indicated that the proposed platform enables SME manufacturers to obtain optimized schedules by solving the job shop scheduling problem(JSSP)by comparing with the real-world data from a textile weaving factory in South Korea.The proposed platform will provide producers with an optimal production schedule,introduce new producers to buyers,and eventually foster relationships and mutual economic interests.
文摘Objective:To investigate the factors contributing to satisfaction with the work environment,job satisfaction(JS),and stress among hemodialysis(HD)staff in the central region of Malaysia.Methods:A quantitative cross-sectional study was conducted on 215 HD staff working at private and non-government(NGO)dialysis centers using self-administered questionnaires.The chi-square test was used to determine factors associated with HD staff's JS,stress,and working environment.Results:The scientific proof was apparent that the working environment had an effect on JS and stress among employees at HD centers.Conclusions:This research offers useful insights into the essence and complexities of HD staff's work and will help nurses,dialysis managers,other dialysis personnel,and organizations to better understand the benefits and stresses faced by these workers.
文摘The Big Five Theory is often regarded as psychology’s most influential personality theoretical approach.The goal of this study is to examine the role of the Big Five Theory in the workplace,especially which personality qualities are more likely to predict work success.Which traits should companies emphasize throughout the hiring and selection processes?How can businesses use the Big Five personality model to locate employees that are more productive,efficient,and devoted to the organization’s goals?A detailed assessment of existing recent research addresses the aforementioned issues.Following a review of many current articles on the subject,it was established that using this model had a positive influence on individual and group performance,working relationships,manager work performance,and workplace innovation.
文摘Saul Bellow’s novel Seize the Day combines the psychological narrative of Jewish immigrants in the“Happy Age”of the United States and the daily life narrative of modern New York urbanites,revealing the living state of modern urbanites-powerless to the outside world,nowhere to live in the material and spiritual world.They have an unresolved personal pursuit and a“dangling”destiny,which alludes to the problems plaguing modern urban people and the decay of American society.By comparing the characteristics and fate of the protagonist Wilhelm with the character Job in the Bible,this article helps to deepen the understanding of the plights of the protagonist as“Modern Job”,and realize the influence of the American urban society on Jewishness and personal survival in that period.
