Repetitive Workload Research Articles

Research on Diagnosis and Localization of Moles for Robotic Mole Removal Surgery Based on YOLO

Surgical treatment is often considered the first choice for mole removal. Treatments such as laser mole removal are widely performed, but intraoperative navigation remains a significant challenge, relying heavily on the experience of surgeons. Additionally, when multiple moles are required to be removed, a more repetitive workload can occur in the surgical procedures. To address these issues, this study aims to achieve precise intraoperative navigation and to achieve modes of automatic diagnosis and localization for robotic mole removal surgery. By training the YOLO model on an open-source categorical mole dataset, this study achieves the automatic diagnosis and localization of the moles during surgeries. In the evaluation of the study, a precision of 0.839 and an average precision mAP of 0.862 which are at a high level are observed. This study verifies that the YOLO can play a critical role in enabling the automatic diagnosis and localization of robotic mole removal surgery.

An Automated Method for Generating Prefabs of AR Map Point Symbols Based on Object Detection Model

Augmented reality (AR) technology enables paper maps to dynamically express three-dimensional geographic information, realizing the fusion of virtual and real information. However, in the current mainstream AR development software, the virtual information usually consists of prefabricated components (prefabs), and the content creation for AR maps heavily relies on manual prefabrication. It leads to repetitive and error-prone prefabrication work, which restricts the design of the dynamic, interactive functions of AR maps. To solve this problem, this paper explored the possibility of automatically generating AR map prefabs using object detection models to establish a data conversion interface from paper maps to AR maps. First, we compared and analyzed various object detection models and selected YOLOv8x to recognize map point symbols. Then, we proposed a method to automatically generate AR map prefabs based on the predicted bounding boxes of the object detection model, which could generate prefabs with corresponding categories and positional information. Finally, we developed an AR map prototype system based on Android mobile devices. We designed an interaction method for information queries in the system to verify the effectiveness of the method proposed in this paper. The validation results indicate that our method can be practically applied to the AR map prefabrication process and can quickly generate AR map prefabs with high information accuracy. It alleviated the repetitive workload established through the manual prefabrication method and had specific feasibility and practicality. Moreover, it could provide solid data support for developing dynamic interactive functions of AR maps.

Research on the data collection standardization system of capacity construction report in changqing oilfield

The capacity construction project group of Changqing oilfield needs to repeatedly enter the same data into multiple different information systems of the company every day. This work mode causes many problems, such as multiple entries, heavy repetitive workload, and difficult to guarantee data quality. Through in-depth analysis of business process and data entry status of the capacity construction project group, this paper puts forward the working ideas of data collection link standardization and data collection standard standardization, explores and establishes a standardized data collection system for the whole chain of capacity construction report data, including investment plan, well information entry, investment allocation, predrilling, drilling, well log, logging, oil testing (gas testing), production and injection, and well delivery. The system guarantees the timeliness, integrity and accuracy of data. In addition, it provides an external data sharing service, build the capacity construction data sharing platform, and realize the “one-time data entry, multiple system reuse, automatic report generation” of capacity construction report data.

Fast parameterized fractal modeling of active heat transfer channel

This paper presents a fast parameterized modeling method for fractal channel and constructs a unified parametric model for Y-shaped, V-shaped, T-shaped fractal channels. This parametric model establishes the relationship between multiple parameters (levels ratio, bifurcation level, pipe diameter ratio, bifurcation angle, aspect ratio) and performance of fractal channel. Parameterized modeling method can reduce repetitive workload and time, improve efficiency. Meanwhile, parametric model allows for a more comprehensive study, and it is important for reduce the occasionality of results. Using the parameterized modeling method, the aspect ratio and fractal channel type are numerically studied. The numerical study of the aspect ratio reveals that with the increase of aspect ratio, Nusselt number decreases, the peak temperature rises and then falls, and the pressure drop first decreases and then increases. The numerical study of fractal channel types shows that the V-shaped channel has the best cooling performance and Y-shaped channel has the best flow performance. Compared to the T-shaped channel, Nusselt number of V-shaped channel increases by 11.29%∼19.74%, the thermal resistance of V-shaped channel decreases by 8.18%∼19.73%, and the pressure drop of Y-shaped channel decreases by 51.04%∼61.75%. The fractal channel parametric model can be applied not only for parameter studies, but also for parameter optimization.

Research on the application of intelligent speech recognition technology in medical big data fog computing system

ABSTRACT Through the establishment of a voice database and voice recognition model, combined with voice recognition processing methods, an intelligent voice recognition input system with medical big data and fog computing as the scene is developed to realise the application of intelligent voice recognition technology in the system, which can reduce the medical staffdaily burden, reduce repetitive workload, and improve the quality and efficiency of clinical work. Based on the key technologies of intelligent voice recognition and medical big data, combined with the characteristics of fog computing, the development of electronic medical records and examination reports intelligent voice entry, mobile nursing intelligent voice entry, non-contact intelligent voice data interaction system, through the construction of fog computing model, design and develop an intelligent medical system to realise the rapid input and output of medical records and examination reports, reduce the workload of doctors and nurses, and concentrate their limited time on the treatment process itself. At the same time, according to the working characteristics of different medical departments, the intelligent system design adopts convenient, practical and efficient intelligent speech recognition technology application tools, and makes full use of big data technology and fog computing architecture to improve speech recognition rate, reduce network delay, and improve query efficiency, It is beneficial to assist the work of various clinical departments, better improve the treatment effect and innovate new medical models.

Experimental study on human physiology during repetitive workload simulated under high temperature and high relative humidity

Repetitive workload may cause fatigue and contributed to most cases of workplace related ergonomics injuries in the industries. The purpose of this study is to investigate the physiological responses induced by the repetitive lifting activities based on in the Malaysia construction workers being exposed under high heat and the relative humidity. To achieve the objectives, three male workers participated in this experiments. There were repeated experimental based on the Design of Experiments procedure simulated under environmental temperature (32°C and 25°C) and repetitive lifting task (15 min). The physiological responses measured where the heart rate (HR) and maximum oxygen consumption (VO2max). The experiments were conducted in a thermal climate simulation chamber and the parameters were set-up based on the real working environment. The results showed that the subjects highly experiencing fatigue when they were exposed to high temperature at 32°C. These phenomena were determined through their HR and VO2max, which were increased gradually under prolonged environment exposure. This study found that the significant heat stress increased the workload intensity in repetitive lifting tasks significantly correlated with the physiological responses of the subjects represented through the HR and VO2max. The study concluded the need of management to reconsider the impact of work environmental temperature and relative humidity to their workers especially to those work under tropical climate.

Is Repetitive Workload a Risk Factor for Upper Extremity Musculoskeletal Disorders in Surgical Device Mechanics? A Cross-Sectional Analysis.

To assess the prevalence of upper extremity work-related musculoskeletal disorders (WMSDs) among surgical device mechanics compared to a control group, a total of 70 employees were included and assigned to three occupational groups (grinders, packers, and control). Personal factors, work exposure, manual skill, and complaints were assessed by two self-administered questionnaires and an industry test. WMSDs were diagnosed in a standardised clinical examination. The two-one-sided t-tests (TOST) procedure was used to test the clinical equivalence of the respective grinding and packaging groups vs. the control group in terms of the Disabilities of the Arm, Shoulder and Hand (DASH) score. Thirty-nine study participants (56%) experienced at least one WMSD at the elbow, forearm, and/or wrist, mainly with signs of epicondylitis and nerve entrapment at the medial elbow. The risk of grinders developing upper extremity WMSD was about 2.5-times higher and packers had an 8.6-fold higher risk of a clinically relevant DASH > 29 compared to the control group. However, these differences were not statistically significant. The groups were also proven to be clinically equivalent in terms of DASH score. Surgical device mechanics do not seem to have worse DASH values or be at higher risk of upper limb WMSDs compared to a control group. This is the first study to analyse and compare different workplaces in this industry that are also common in other industries.

THE STUDY OF WORK BEHAVIOURS AND RISKS FOR OCCUPATIONAL OVERUSE SYNDROME

"Occupational overuse syndrome" is defined as the syndrome of work-related musculoskeletal disorders resulting from repetitive hand posture and motion. We looked at 867 employees in seven different factories to determine the groups suffering from trigger fingers, de Quervain's disease and carpal tunnel syndrome (CTS) from the period of January 2009 to November 2010. The inclusion and exclusion criteria were designated for the subjects in each group. We found the highest prevalence of the syndrome in the rate of CTS development. The differences in the hand spans and the grip strengths between the normal versus the diseased groups were statistically significant. The most common work patterns were a repetitive workload with the hand in a posture of a contracted grasping position. This accounted for 43.1% of the cases of trigger fingers, 38.1% in cases of CTS and this position with a contributing increased speed in the work pattern at 29.8% in the de Quervain's disease patients.

The Application of Computers in Health Physics

The use of computers in increasing the flexibility of a radiation protection system and in reducing the repetitive work load on technical staff is discussed in relationship to the CERN Super Proton Synchrotron. The SPS Radiation Control System is described, showing the interdependence of the instruments and their related software.