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2018
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28 pages
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Global Academic Journal of Medical Sciences, 2022
Musculoskeletal disorders (MSDs) are collectively referring to an array of conditions affecting the human locomotor system, such as muscles, nerves, joints, tendons and spinal discs. MSDs related to work are called occupational MSDs and are typically caused by physical factors consisting of repetitive tasks, forceful exertions, awkward positions, vibration due to use of vibrational tools and prolonged staying in the same positions. These physical factors are often complicated by psychosocial factors comprising job demand, job control, social support, job satisfaction, job security, work arrangement, etc. which can aggravate the biomechanical loading imposed by physical factors, thus resulting in more severe outcomes. Besides, individual factors such as health conditions, age, education level and medical history could lead to highly variable physiological responses and internal tolerances, hence outcomes. As the physical and psychosocial risk factors vary widely in different workplaces, the prevalence of MSDs tends to vary with sectors, occupations and even regions. Generally, healthcare sector has been reported to have relatively high occupational MSDs cases in multiple nations. To prevent occupational MSDs, priority should be given to elimination of the associated risks through job and workplace designs and management. Where elimination is not practical, the risks could be reduced through modification of workplace layout, work environment, work systems and tools as well as the use of mechanical aids. Provision of information, instruction and training, and other administrative controls such as job rotation which do not target at reducing the risks would have lower priority and should be used together with other control measures of higher priority.
2009
Research has shown that an ergonomics process that identifies risk factors, devises solutions to reduce musculoskeletal disorders (MSDs), and evaluates the effectiveness of the solutions can lower worker exposure to risk factors and MSDs and improve productivity. A review of the Mine Safety and Health Administration (MSHA) injury/illness database indicated that 46% of illnesses in 2004 were associated with repetitive trauma and 35% of nonfatal lost days involved material handling during 2001-2004. Even though these statistics show that MSDs significantly contribute to occupational illnesses and injuries in the U.S. mining industry, few mining companies have implemented an ergonomics process. Despite the many unique challenges in the mining environment, three mining companies partnered with the MSD Prevention Team at the National Institute for Occupational Safety and Health's Pittsburgh Research Laboratory to demonstrate that an ergonomics process could be systematically implemented and effectively integrated with existing safety and health programs. Because these three mining companies were very different in organization, culture, and size, the ergonomics processes had to be modified to meet the needs of each company. A description of how these three companies applied ergonomics and the tools and training used to implement their processes is given. Prior to discussing the case studies, general information on the elements of an ergonomics process is provided. YELLOW INSERT SHEET Section I Introduction: Ergonomics and Risk Management Ergonomics is the scientific discipline concerned with the understanding of interactions among people and other elements of a system to optimize their well-being and overall system performance [IEA 2008]. This is generally accomplished by applying ergonomic principles to the design and evaluation of manual tasks, 1 1 Manual tasks are tasks that involve lifting, pushing, pulling, carrying, moving, manipulating, holding, pounding, or restraining a person, animal, or item. jobs, products, environments, and systems, ensuring that they meet the needs, capabilities, and limitations of people. When integrated with safety and health programs, ergonomics can be viewed as a third leg of a three-pronged risk management approach to reduce musculoskeletal disorder (MSD) rates. Safety focuses on hazards that may result in traumatic injuries, industrial hygiene concentrates on hazards that may cause occupational disease, and ergonomics addresses risk factors that may result in MSDs and other conditions, such as vibration-related illnesses. By applying ergonomic principles to the workplace with a systematic process, risk factor exposures are reduced or eliminated. Employees can then work within their abilities and are more efficient at performing and completing tasks.
Journal of Occupational Rehabilitation, 1992
There is a large and increasing incidence of work-related muscoloskeletal disorders, both upper extremity cumulative trauma disorders and low back pain. Several occupational risk factors have been linked with the development of musculoskeletal disorders. In order to identify the known occupational risk factors associated with a specific job, an analysis procedure is described to help identify ergonomic risk factors in the workplace. Job analysis shouM be one part of an overall ergonomics control program. Once the ergonomic risk factors have been documented, the ergonomics committee can use that information to begin developing solutions that will decrease or eliminate the identified risk factors. When placing a worker who is returning to the workforce after recovering from an injury, health care professionals can also use the information from the job analysis to assist in matching up task demands with worker capabtTities and limitations.
Health Scope, 2015
Background: Work-related musculoskeletal disorders (WMSDs) are one of the most important factors for occupational injuries and disabilities, with the back injuries being the most common work-related injuries in different industries in many developing countries. Objectives: The objectives of the present study were determination of the prevalence of WMSDs symptoms, identification of major risk factors associated with WMSDs symptoms and ergonomics interventions to reduce these disorders. Patients and Methods: This follow-up and interventional study was carried out in a lead mine. Forty persons participated in this study. The Nordic musculoskeletal questionnaire was used to study the prevalence of WMSDs and the quick exposure check (QEC) method was used to assess the physical exposure to risks. Ultimately, data was analyzed using McNamar's and Cochran's tests by SPSS version 11 software. Results: The results revealed that the highest prevalence of musculoskeletal disorders was reported in lower back (57.5%) and knees (50%) during the 12 months prior to the study. After ergonomics interventions, significant reductions in WMSDs were observed at the time of follow-up. According to Cochran's test, significant differences between the pre, four and nine months after the intervention in lower back and knee were observed (P < 0.005). Conclusions: Consistent reductions were observed for all WMSDs disorders at the ninth month of the follow-up. It can be inferred that the use of practical and low-cost methods of engineering and administrative interventions together and monitoring the proper implementation of these interventions during a long time may achieve desired results in reducing musculoskeletal disorders in small scale and poor industries in developing countries.
Human Factors the Journal of the Human Factors and Ergonomics Society, 2014
To better characterize associations between physical risk factors and upper-extremity musculoskeletal symptoms and disorders, a prospective epidemiologic study of 386 manufacturing workers was performed. Background: Methodological limitations of previous studies have resulted in inconsistent associations. Method: An individual, task-based exposure assessment strategy was used to assess upper-extremity exertion intensity, repetition, and time-in-posture categories. Participants recorded time spent performing daily work tasks on a preprinted log, which was then used to calculate time-weightedaverage exposures across each week of follow-up. In addition, a weekly Strain Index (SI) risk category was assigned to each participant. Incident musculoskeletal symptoms and disorders were assessed weekly. Proportional hazards analyses were used to examine associations between exposure measures and incident hand/arm and neck/shoulder symptoms and disorders. Results: Incident symptoms and disorders were common (incident hand/arm symptoms = 58/100 person-years (PY), incident hand/arm disorders = 19/100 PY, incident neck/shoulder symptoms = 54/100 PY, incident neck/shoulder disorders = 14/100 PY). Few associations between separate estimates of physical exposure and hand/arm and neck/shoulder outcomes were observed. However, associations were observed between dichotomized SI risk category and incident hand/arm symptoms (hazard ratio [HR] = 1.73, 95% confidence interval [CI] = [0.99, 3.04]) and disorders (HR = 1.93, 95% CI = [0.85, 4.40]). Conclusion: Evidence of associations between physical risk factors and musculoskeletal outcome was strongest when exposure was estimated with the SI, in comparison to other metrics of exposure. Application: The results of this study provide evidence that physical exposures in the workplace contribute to musculoskeletal disorder incidence. Musculoskeletal disorder prevention efforts should include mitigation of these occupational risk factors.
ACTAS XVI CONGRESO NACIONAL DE NUMISMÁTICA Tesoros y hallazgos monetarios: protección, estudio y musealización, 2021
El objetivo de este texto es ofrecer un ensayo de síntesis sobre la relación entre las diferentes condicio- nes que determinaron el ejercicio del poder en diversos contextos políticos peninsulares de época medieval, por un lado, y las características de los registros numismáticos generados en estos contextos, por otro. Estas condiciones afectaron a la composición y a la distribución temporal y geográfica de estos registros. Entre los aspectos que serán explorados desde una perspectiva comparativa, destacan la relación entre los hallazgos monetarios y la variable capacidad de exigir pagos con monedas por parte de diferentes poderes políticos medievales; con la diversidad de los sujetos obligados a efectuar estos pagos; con el alcance y con el volumen de los intercambios en los que intervinieron las monedas, y con la ideología transmitida por las monedas utilizadas y acumuladas. Los registros numismáticos sobre los que se basará este ensayo comparativo corresponden a diferentes contextos políticos, mayormente peninsulares, comprendidos entre los siglos VI y XVI.
El proyecto de un sistema hidráulico, comprende el diseño, selección de materiales y construcción del pistón hidráulico, circuito hidráulico y el ensamble con la bomba y accesorios, este equipo será accionado por la fuerza de un fluido en movimiento, cuya aplicación es en los dispositivos de máquinas herramientas, estampado, perforación, empaques y otras.
Sakarya Üniversitesi Fen Bilimleri Enstitüsü dergisi/Sakarya Üniversitesi fen bilimleri enstitüsü dergisi, 2023
Electronic Electronic messages, i.e. e-mails, are a communication tool frequently used by individuals or organizations. While e-mail is extremely practical to use, it is necessary to consider its vulnerabilities. Spam e-mails are unsolicited messages created to promote a product or service, often sent frequently. It is very important to classify incoming e-mails in order to protect against malware that can be transmitted via e-mail and to reduce possible unwanted consequences. Spam email classification is the process of identifying and distinguishing spam emails from legitimate emails. This classification can be done through various methods such as keyword filtering, machine learning algorithms and image recognition. The goal of spam email classification is to prevent unwanted and potentially harmful emails from reaching the user's inbox. In this study, Random Forest (RF), Logistic Regression (LR), Naive Bayes (NB), Support Vector Machine (SVM) and Artificial Neural Network (ANN) algorithms are used to classify spam emails and the results are compared. Algorithms with different approaches were used to determine the best solution for the problem. 5558 spam and non-spam e-mails were analyzed and the performance of the algorithms was reported in terms of accuracy, precision, sensitivity and F1-Score metrics. The most successful result was obtained with the RF algorithm with an accuracy of 98.83%. In this study, high success was achieved by classifying spam emails with machine learning algorithms. In addition, it has been proved by experimental studies that better results are obtained than similar studies in the literature. 1. Introduction With the widespread use of the Internet, electronic communication has become more preferred. One of the most important tools of electronic communication is electronic messages, which we call e-mail. Today, individuals or organizations have one or more email accounts. Instant delivery of messages, no cost and ease of use increase the importance and prevalence of e-mail [1]. According to Statista Research Department data, the number of actively used e-mail accounts in 2020 is more than 4 billion. This number is estimated to increase to 4.6 billion in 2025. In 2020, 306 billion e-mails are sent and received every day, and this number is expected to exceed 376 billion in 2025 [2]. The use of e-mail is not only practical but also has various vulnerabilities. The e-mail account to be hijacked in various ways, for e-mails containing advertisements etc. to hijack your computer by installing a software on your computer when you click on the advertisement, and for the installed software to disrupt communication by sometimes filling the
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