Real Working Environment Research Articles

108 Can Low-Cost Sensor Networks Help Occupational Hygiene?

Abstract This study aims at achieving a better picture of the spatial and temporal distribution of industrial pollutants in the working environment. We explore the utilization of this information in occupational hygiene practice by developing and building a low-cost sensor network in multiple real working environments. Sensor networks were installed in different scenarios: in- and outdoors of a steel factory and on a cruise ship’s car deck. The stationary sensor networks are composed of multiple custom sensing nodes. Each node is equipped with various low-cost sensors to assess gaseous components, dust particles, temperature, and humidity. Additionally, measurements using validated traditional occupational hygiene methods and high end portable direct-reading instruments (DRIs) are performed stationary and mobile. Mobile devices carried by the workers in the breathing zone complement the measurements by the stationary sensor network. The results consist of evaluations carried out through combining the sensor data, contextual information and the results obtained with traditional occupational methods. Can this data fusion be used to assess exposure, and target risk management measures? In this work, we discuss the feasibility of the available sensors for industrial measurements and further explore the suitability of pollutant concentration maps for exposure assessment and for planning control measures.

AI in Process Industries – Current Status and Future Prospects

AbstractThe chemical industry is one of the key industrial sectors in Germany and at the same time one of the largest consumers of energy and raw materials. A successful energy transition and the development of a circular economy can only succeed if they are actively supported and shaped by the chemical industry – through the redesign of existing production processes and the exploration and implementation of new process routes. The challenge is to realize this transformation within a very short time and for many production processes, whereby a much larger number of process routes must be explored. Digital technologies are key to master this transformation towards more sustainability, climate, and environmental protection. The KEEN project aims to explore and leverage artificial intelligence (AI) opportunities in process industry. The newly developed AI methods are tested wherever possible in real working environments and production plants to prove the economic benefit, applicability, and reliability of the methods and technologies.

An integrated energy recovery system for productive biogas applications: Continuous mode operation and assessment

The application of biogas as a renewable energy source continues to face competition from conventional energy sources, which are readily available and seemingly cheap. In addition, productive biogas system deployments in Uganda are currently facing challenges related to sustainability of biogas production, which has led to massive dis-adoption in recent years. These systems have failed to utilize alternatives during scarcity of primary feedstock due to lack technical data for energy recovery, which could be linked to insufficient R&D in the biogas sector. Relatedly, global scientific research has placed focus mostly on methane yield improvements through optimization of anaerobic digestion kinetics on lab-scale, with little focus on the enabling environment for these kinetics to thrive in continuously operated systems.This study therefore aimed to develop an integrated energy recovery system that enables alteration of feedstock and control of digester operating parameters for sustainable biogas production in continuously fed digesters. An array of system components was developed and integrated into a state-of-art energy recovery system, which was prototyped and deployed in real working environment for pilot studies. The system was configured to measure the moisture content of the feedstock and then determine and display to the operator the amount of water to be added to optimize the quality of the substrate. The system also monitors the digester operating parameters and prompts corrective action to prevent possible inhibition of biogas production process. Results show that the system is about 33% more efficient than the conventional one, allows alteration of feedstocks, and can be deployed to replace conventional energy usage for productive applications. For instance, a poultry farm with 10,000 commercial layers may have its energy needs be met 100% by the proposed system with a pay-back period of 4.5 years for deep liter system and 3.7 years for battery cage system.

Enhancing Medical Students’ Knowledge and Performance in Otolaryngology Rotation through Combining Microlearning and Task-Based Learning Strategies

Microlearning is recommended to be implemented within the context of a wider teaching-learning ecosystem, especially in real working environments. Task-based learning is used in clinical education setting. This study aims at assessing the effect of an integrated approach of microlearning with task-based learning on medical students' knowledge and performance in Ear, Nose and Throat clerkship rotation. A total of 59 final-year medical students participated in this quasi-experimental study which included two control groups (routine teaching and task-based learning methods) and one intervention group (combined microlearning and task-based learning method). Pre- and post-tests of students' knowledge and performance were assessed through a multiple-choice question test and a Direct Observation Procedural Skills (DOPS) instrument, respectively. Performing Analysis of Covariance for knowledge post-test scores among three groups revealed significant differences (F = 3.423, p-value = 0.040) and the intervention group had the highest score. Analyzing DOPS results showed that the intervention group achieved significantly higher scores compared to the control ones for all the expected tasks (p-values = 0.001). The findings of the present study show that the combined strategy of microlearning with task-based learning is an effective clinical teaching method for enhancing medical students' knowledge and performance in a real working environment.

Transfer Learning-Based Intelligent Fault Detection Approach for the Industrial Robotic System

With increasing customer demand, industry 4.0 gained a lot of interest, which is based on smart factories. In smart factories, robotic components are vulnerable to failure due to various industrial operations such as assembly, manufacturing, and product handling. Timely fault detection and diagnosis (FDD) is important to keep the industrial operation smooth. Previously, only the unloaded-based FDD algorithms were considered for the industrial robotic system. In the industrial environment, the robot is working under various working conditions such as speeds, loads, and motions. Hence, to reduce the domain discrepancy between the lab scale and the real working environment, we conducted experimentations under various working conditions. For that purpose, an extensive experimental setup is prepared to perform a series of various experiments mimicking the real environmental condition. In addition, in previous research work, various machine learning (ML) and deep learning (DL) approaches were proposed for robotic arm component fault detection. However, various issues are related to the DL and ML approaches. The ML models are problem-specific, and complex in computations. The DL model needs a huge amount of data. The DL model is composed of various layers that have not been thoroughly explored; as a result, the fault detection model lacks a comprehensive explanation. To overcome these issues, the transfer learning (TL) model is considered with the diverse experimental scenarios. The main contribution is to increase the generalization capabilities of the robotic PHM in the context of previously available research work. For that purpose, the VGG16 model is used because of its autonomous feature extractions for fault classification. The data are collected under a variety of different operating conditions such as loadings, speeds, and motion patterns. The 1D signal is converted to a 2D signal (scalogram) to perform the TL model. The proposed approach shows effective fault detection performance and has the capabilities of generalization under variable working conditions.

Novel Design of Assistive Technologies Based on the Interconnection of Motion Capture and Virtual Reality Systems to Foster Task Performance of the Ageing Workforce

Demographic changes, increasing life expectancy, and increasing healthy life expectancy lead to an increasingly ageing workforce. This condition has a growing impact on the workforce in today’s industries. However, old workers are not a burden for companies and industries. They are a fundamental part of the industrial ecosystem due to the consistency of their human factors, namely their large knowledge, experience, and decision-making ability. For this reason, the ageing workforce must be incorporated and engaged through the introduction of digital age technologies to improve their working conditions and extend their active life. This paper focuses on a novel design of assistive technologies based on the interconnection of motion capture (MoCap) and virtual reality (VR) systems as a driver for the improvement of the task performance of the ageing workforce. We intend to explore how this technological tool can help and enhance the work of the ageing workforce. For this, we study two different areas of application: the training, learning, and communication of the older workers and the ergonomic analysis and workplace design for the ageing operators. In the end, a pilot study is proposed to apply this technology in real work environments.

Метакогнитивни проекции на лингво-литературния дидактически тренинг в дигитална среда при бъдещи начални учители

The article examines parameters in the implementation of digital training in the field of linguistic-literary didactic discourse. It is included in the educational process of students from pedagogic specialties who study at Trakia University – Stara Zagora, Bulgaria. Descriptive statistics were used to present the identified metacognitive strategies for the realized simulation form – an analogue of the lesson in a real work environment. They can relate to the analyzing, creating and evaluating through testifying to the realized reflection of future elementary teachers. Problems related to goal setting and time distribution of educational activities were registered, as well as when outlining the parameters of an imaginary communicative speech situation. A high level was found in the self-assessment of pedagogical students regarding the implemented simulation form in a digital environment.

Shaping sustainable development competencies through student internships

Purpose: One of the most important challenges of civilization in the contemporary world is obtaining the goals of sustainable development. This challenge is addressed to present and future generations who have to possess or acquire various sustainable development competencies. Shaping them is particularly essential in the case of generation Z, thus it should take place both in the process of academic education, as well as in cooperation with university stakeholders. The aim of the paper is to answer the question of whether the implementation of students’ internships enables shaping sustainable development competencies. Design/methodology/approach: The survey was conducted in Poland in 2022 among 367 full- time students in the management field of study. The CAWI method was used. The paper presents a quantitative analysis of the obtained data. In the theoretical part of the article, the author explained the essence and goals of sustainable development, described sustainable development competencies, and the role of higher education and stakeholders in shaping the SD competencies of Generation Z. Findings: Generation Z has a positive attitude towards the implementation of the concept of sustainable development and almost all of the studied sustainable development goals are of great importance to the respondents. The obtained results confirmed that the implementation of internships in a real work environment affects the shape of many SD competencies of students. The greatest opportunities for the development of SD competencies were provided to interns by business organisations and administration, while less importance was assigned to such stakeholders as NGOs. Students expect the cooperation of the university and its stakeholders in shaping their SD competencies. Research limitations/implications: The size of the surveyed group does not allow for the formulation of general conclusions. However, the obtained results may be the basis for further in-depth studies on the problem. Similar research could be conducted to establish the opinion of employers and university representatives with a broader consideration of other variables. Practical implications: The conclusions of the study will provide universities and various stakeholders with valuable information on the possibility of using student internships to develop SD competencies of representatives of Generation Z. Originality/value: The obtained results allow one to fill the research gap concerning the assessment of whether the realization of student internships in a real work environment enables shaping students' competencies in the field of sustainable development. Keywords: sustainable development, sustainable competencies, green competencies, education for sustainable development, internships, stakeholders, business students, Generation Z. Category of the paper: Research paper.

Training simulators for crane operators and drivers

The article deals with the use issues of modern information technology for training purposes. In particular, use of simulation modelling to create a learning environment as close as possible to the real working environment. This helps speed up learning, make more practical, learn theoretical issues directly when mastering practical skills, and make the learning process more attractive and interesting for students. Moreover, a virtual working environment can be used for advanced training of employees, to improve their professional skills, master new technologies, train them to work on new and modernized equipment, assess their professional level, restore skills after a long break in the work and pass qualification exams. Information technologies can significantly reduce the cost of material support for training and eliminate dependence on large areas for staff training. To create an interactive virtual learning environment, modern gaming technologies, software modelling or, at least, simulation modelling of physical processes in equipment and the interaction of all components of the working environment, including the actions of the student, are used. It also allows testing employees in extreme working conditions and testing their skills when dealing with non standard and emergency situations, without any real danger to the health of students. The proposed solution can be used to train students and trainees, assess professional skills of those already working in the conditions of special training centers and professional retraining colleges.

METHODOLOGY FOR CALCULATING THE COST PRICE OF THE BENDING PROCESS FOR THE NEEDS OF MANUFACTURING LOGISTICS

The research of this paper aims to characterize and describe the methodological sequence of operations necessary for the correct calculation of the cost price when performing a bid calculation in the bending process step on a bending machine. The research focuses on determining the methodology and its application exclusively to sheet metal parts in the engineering industry in the processing of steel and stainless-steel sheets. To research this issue, we used empirical and quantitative research in a real work environment. The methodology for calculating the cost price of bending sheet metal parts yields the relationships between component inputs, the result of which is a time parameter that is expressed by the actual production costs. The results can be used in the real working environment of manufacturing companies for comparison with already established practices and a verification of their outputs. At the same time, it is possible to use the determined methodological procedure as a basis for implementation in the Aurendi web application.

Employers’ Feedback on Davao Oriental State College of Science and Technology (DOSCST) Professional School Graduates in their Workplace

This study was conducted to determine how the Davao Oriental State College of Science and Technology (DOSCST) Professional School graduates performed in the real work environment as perceived by their employers. It utilized the quantitative method with 52 employers as the respondents and the qualitative method with 11 employers as the key informants. The study was conducted at the different workplaces of the DOSCST Professional School graduates within the province of Davao Oriental. Findings reveal that the level of employers' satisfaction with the education exemplified by DOSCST Professional School graduates is highly satisfactory. The degree of importance for the successful performance of the graduates in terms of the four indicators: knowledge and understanding of the job, general skills, specialized skills, and qualities of graduates, is extremely important. However, the employers' satisfaction and the DOSCST Professional School graduates' performance indicate an overall significant positive moderate relationship towards each other. Among the demographics given in this study, only the length of service exhibits a significant difference in the employer's satisfaction. Moreover, future researchers may study students' academic performance versus the teaching performance of the DOSCST Professional School graduates. Likewise, they may also look into the ethics and commitment of the teachers who graduated from the DOSCST Professional School.

The Effective methods for managing teachers: A case study on a Private School in Al-Ain, United Arab Emirates.

This article was done to apply the methods and concepts that we learned in the management course. First, we proposed some methods to improve the efficiency of management we studied, then a survey was conducted based on the conditions and our abilities to test the validity of the methods. Moreover, we analyzed the data to figure out that strategies will certainly have a positive influence on the learning process and we decided to accept the alternative hypothesis and reject the null hypothesis. Finally, we would like to say that it was a fantastic opportunity and beneficial one due to the fact that we learned a lot through it.
 This study was conducted to initiate new strategies to manage teachers in Liwa school The main purpose of the study is to provide a chance for practical application of theory in the classroom and to acquire practical knowledge for efficient work in the future. It also provides the interns with more information and knowledge in the real work environment.

Eye-Tracking Active Indicators of Insider Threats: Detecting Illicit Activity During Normal Workflow

Cyber challenges faced by organizations today involve malicious inside actors, often labeled insider threats (ITs). These present a difficult challenge in that the most well-designed cybersecurity apparatus is vulnerable to those inside the organization who have privileged access to information systems. Innovative methods must be developed to help security analysts narrow the large pool of potential ITs in large organizations to a more manageable number. The purpose of this article is to develop and validate eye-tracking metrics that are diagnostic of IT behavior. Key stimuli, or called active indicator probes, were embedded into a simulated workflow to elicit diagnostic eye-tracking responses. Two environments were simulated: financial and intelligence analysis. We evaluated participants performing as regular workers relative to ITs to identify metrics that distinguished between the two groups. Detection of illicit eye gaze behavior while using chat programs was possible when conversations with accomplices occurred in a separate chat window from normal permissible chat conversations. Validation of results in real work environments is necessary for practical application. However, if the approach proves to translate successfully, automated monitoring of eye-tracking responses may augment existing insider detection methods, within frameworks for best practices in organizational security and cyber defense.

Knowmads as Possible Mutants of Knowledge Workers in the Brave post-COVID World

The purpose of the present study is to capture the specific forces that are intensifying in the COVID-19 context, which stimulate the adaptation of some knowledge workers characteristics into mutated traits – the traits of knowmads. Also, the present study aims at exploring how this transformation is presented in the literature. Defined by John Moravec, the term "knowmad" describes those workers that stand out by being proficient in working with anybody, anywhere, at any time. As an autonomous knowledge worker apt to develop business ecosystems in real, virtual, or hybrid working environments, knowmads are not confined to employees of a single organization. A steady evolution in this respect has been visible for the last decade already. Still, it accelerated during COVID-19 pandemics, due to the global economic crisis. Studies show that the trend will continue to develop in the post-pandemic environment, as the prevalence of flexible, remote work during pandemics has increased from a niche occurrence to a widespread practice over the past nearly two years. Because of the COVID-19 pandemic, an unprecedented number of employees worked from remote locations, on flexible schedules, and were not under the direct control of their supervisors. This study aims to explore and capture the main forces powered by COVID-19 pandemics, which stimulated the change of certain knowledge workers characteristics into a mutation towards knowmads characteristics. The authors implemented a critical literature analysis, and a computer-aided bibliometric analysis performed with the help of VOSviewer version 1.6.17 software. Findings demonstrate that the COVID-19 context boosted the transformation of the knowledge workers into knowmads, and the process is not going to end soon. Also, the search performed with VOSviewer shows a significant absence of knowledge concerning the transformation of corporate knowledge workers into self-managed knowmads.

Sustainable career and employability of student leaders in China.

Research has shown that most employers prefer employing graduates with student leadership experience in colleges and most of the student leaders have sustainable development in their careers in China. Compared with students without leadership experience, student leaders are easier to get promotion and development opportunities in the workplace. To discuss this question, researchers chose employers, student leaders, and teachers as research participants in an effort to answer the question of why employers prefer graduates with experience being student leaders. This study focuses on what key competencies student leaders possess and how their competencies can match the capability requirement of employers. Semi-structured interviews were conducted with 9 outstanding student leaders, 4 class teachers, 2 student affairs administrators, and 8 human resource managers from two vocational colleges in Beijing. We find that student leaders have strong social competence, emotional competence, action competence, responsibility, and resilience which employers value and these competencies are essential to career development in the workplace. These competencies are considered to be helpful to support student leaders to adapt to the real work environment quickly and achieve career success.

Vocational Training With Microlearning—How Low-Immersive 360-Degree Learning Environments Support Work-Process-Integrated Learning

In-company training is facing new challenges in preparing employees for the demands of digitalized and automated manufacturing. New training concepts like microlearning are necessary to support work-process-related learning. To handle the limitations of microlearning, we develop a 360-degree learning system to demonstrate a realistic work environment and overcome the lack of design knowledge supporting the motivation and performance of employees using such systems. Based on a systematic literature review and semistructured interviews, we have developed design requirements for interactive 360-degree learning environments. We used a workshop-based mixed-method approach with interviews, concept maps, and video analysis to evaluate the motivation and performance of precision mechanics within a prototypical work-process-oriented learning environment in an intercompany vocational training center. The results show a positive effect on learning outcomes and motivation. In addition, the ease of use and sense of presence while using the learning environment are rated as high. We contribute to theory by shedding new light on learners’ motivation and performance within work-process-oriented interactive 360-degree learning environments. Furthermore, we offer guidelines for developing interactive 360-degree learning environments against the background of the current metaverse discussion.

Electrolyte additive engineering for aqueous Zn ion batteries

Aqueous Zn ion batteries (AZIBs) are one of the most promising new-generation electrochemical energy storage devices with high specific capacity, good security, and economic benefits. The electrolyte acts as a bridge connecting cathode and anode, providing a realistic working environment. However, using aqueous electrolytes presents many challenges for cathode (dissolution, electrostatic interaction, by-products) and anode (Zn dendrite, side reactions). As an innovative and maneuverable technology, additive engineering has effectively solved electrodes' critical problems. Therefore, it is essential to systematically summarize additive engineering and explore new perspectives in response to the existing issues. Based on the challenges of electrolytes for electrodes, the review focuses on an overview of the effects of additive engineering on cathode and anode, respectively. Additive engineering can improve the problems existing in the cathode, such as relieving dissolution, adjusting electrostatic interaction, and reducing by-products. The effects on anode are summarized in aspects of inhibiting Zn dendrites and reducing side reactions. In addition, the effects of different additives on the charge storage mechanism as well as the kinetic characteristics of AZIBs are described separately. Finally, the potential directions and development prospects for further improvement of additive engineering in AZIBs are proposed. In this review, we retrospect the challenges faced by the cathode and anode of AZIBs during the use of aqueous electrolytes. As an innovative and maneuverable technology, additive engineering can be used to effectively solve most of the critical problems of cathode and anode. Thus, a comprehensive overview of additive engineering strategies is presented from a new perspective of function and mechanism. Finally, potential directions and development prospects for further improvement of additive engineering in AZIBs are presented based on the authors’ best knowledge.

Polycyclic aromatic hydrocarbon exposure and DNA oxidative damage of workers in workshops of a petrochemical group.

The petrochemical industry has promoted the development of economy, while polycyclic aromatic hydrocarbons (PAHs) produced by the industry become the threat for environment and humans. Data on human occupational exposure in petrochemical industry are limited. In the present study, urinary hydroxylated PAH metabolites (OH-PAHs) and a biomarker of DNA oxidative damage (8-hydroxy-2'-deoxyguanosine (8-OHdG)) were measured in 546 workers of a petrochemical group in Northeast China, to investigate PAH exposure and related potential health risk. The concentrations of ∑9OH-PAH in all workers were 0.25-175μg/g Cre with a median value of 4.41μg/g Cre. Metabolites of naphthalene were the predominant compounds. The levels of PAH metabolites were significantly different for workers with different jobs, which were the highest for recycling workers (13.7μg/g Cre) and the lowest for agency managers (5.12μg/g Cre). Besides, higher levels of OH-PAHs were usually found in males and older workers. There was a dose-response relationship between levels of 8-OHdG and ∑9OH-PAHs (p<0.01). No difference was observed in concentrations of 8-OHdG for workers of different gender or ages, work history as well as noise. Furthermore, workers simultaneously exposed to other potential pollutants and higher levels of ∑9OH-PAH had significantly higher levels of 8-OHdG compared with those in the corresponding subgroups. Our results suggested that exposure to PAHs or co-exposure to PAHs and potential toxics in the petrochemical plant may cause DNA damage. We call for more researches on the associations among noise, chemical pollution and oxidative stress to workers in the real working environment.

Facilitators and barriers of African postgraduate nursing students' adaptation to internship: A qualitative study

BackgroundClinical internship is a focused and supervised practice where nursing students have opportunities to master clinical skills and better adapt to the real working environment, promoting the formation of professional practice quality. However, for African postgraduate nursing students who had an internship in China, the factors affecting their adaptation to the internship have not yet been sufficiently explored. ObjectiveTo explore the facilitators and barriers of African postgraduate nursing students' adaptation to an internship. DesignQualitative descriptive study. SettingsA comprehensive university with three affiliated hospitals in southern China. ParticipantsTwelve African postgraduate nursing students who finished a three-month internship in the two-year postgraduate programme. MethodsParticipants were recruited using purposive sampling. Semi-structured interviews were conducted between April and December 2021. Data were thematically analysed using the Colaizzi seven-step method. ResultsThree facilitators and four barriers to their adaptation to the internship emerged in the study. Facilitators included the teacher–student interactions, harmonious working atmosphere and positive inner incentives of the students. Barriers to adaptation were language barriers, unsuitable internship arrangements, lack of opportunities to practice clinical skills and disparities in hospital routine works. ConclusionsThe present findings could contribute to the improvement of a more effective clinical training programme. Nursing colleges and teaching hospitals should make more efforts to enhance the current clinical internship programmes. Further support is necessary for international nursing students according to their culturally and linguistically diverse backgrounds.

A novel platform to enable the future human-centered factory

This paper introduces a web-platform system that performs semi-automatic compute of several risk indexes, based on the considered evaluation method (e.g., RULA—Rapid Upper Limb Assessment, REBA—Rapid Entire Body Assessment, OCRA—OCcupational Repetitive Action) to support ergonomics risk estimation, and provides augmented analytics to proactively improve ergonomic risk monitoring based on the characteristics of workers (e.g., age, gender), working tasks, and environment. It implements a body detection system, marker-less and low cost, based on the use of RGB cameras, which exploits the open-source deep learning model CMU (Carnegie Mellon University), from the tf-pose-estimation project, assuring worker privacy and data protection, which has been already successfully assessed in standard laboratory conditions. The paper provides a full description of the proposed platform and reports the results of validation in a real industrial case study regarding a washing machine assembly line composed by 5 workstations. A total of 15 workers have been involved. Results suggest how the proposed system is able to significantly speed up the ergonomic assessment and to predict angles and perform a RULA and OCRA analysis, with an accuracy comparable to that obtainable from a manual analysis, even under the unpredictable conditions that can be found in a real working environment.