ABSTRACT
By observing the actions taken by operators, it is possible to determine the risk level of a work task. One method for achieving this is the recognition of human activity using biosignals and inertial measurements provided to a machine learning algorithm performing such recognition. The aim of this research is to propose a method to automatically recognize physical exertion and reduce noise as much as possible towards the automation of the Job Strain Index (JSI) assessment by using a motion capture wearable device (MindRove armband) and training a quadratic support vector machine (QSVM) model, which is responsible for predicting the exertion depending on the patterns identified. The highest accuracy of the QSVM model was 95.7%, which was achieved by filtering the data, removing outliers and offsets, and performing zero calibration; in addition, EMG signals were normalized. It was determined that, given the job strain index's purpose, physical exertion detection is crucial to computing its intensity in future work.
Subject(s)
Ergonomics , Physical Exertion , Humans , Electromyography/methods , Ergonomics/methods , Algorithms , Machine LearningABSTRACT
Energy harvesting shock absorbers (EHSA) have made great progress in recent years, although there are still no commercial solutions for this technology. This paper addresses the question of whether, and under what conditions, an EHSA can completely replace a conventional one. In this way, any conventional suspension could be replicated at will, while recovering part of the wasted energy. This paper focuses on mimicking the original passive damper behavior by continuously varying the electrical parameters of the regenerative damper. For this study, a typical ball-screw EHSA is chosen, and its equivalent suspension parameters are tried to be matched to the initial damper. The methodology proposes several electrical control circuits that optimize the dynamic behavior of the regenerative damper from the continuous variation of a load resistance. The results show that, given a target damper curve, the regenerative damper can adequately replicate it when there is a minimum velocity in the damper. However, when the damper velocity is close to zero, the only way to compensate for inertia is through the introduction of external energy to the system.
Subject(s)
RotationABSTRACT
We describe a new species of diurnal gecko, Gonatodes castanae sp. nov. from the foothills of the Serranía de San Lucas, municipality of Norosí, Department of Bolívar, Colombia. The new species differs from all species in the genus by the combination of the following characters: moderate size, subcaudal scale pattern type B (1'1'1''), typically two rows of lateral scales on the digits, and aspects of color pattern in males (dorsum, flanks, limbs and tail with white ocelli on a black background) and females (dorsum, flanks, limbs and tail with brown to black reticulations and withe spots on a greenish-yellow background). The validity of the new species is also supported by molecular analyses. This species inhabits relicts of riverine forests at about 150 m above sea level (a.s.l.). Gonatodes castanae increases the number of known species in this genus to 34 and the species registered for Colombia to eight.
Subject(s)
Lizards , Animal Distribution , Animal Structures , Animals , Colombia , Female , Forests , MaleABSTRACT
We design and fabricate elastically tunable monodisperse microcapsules using microfluidics and cross-linkable polydimethylsiloxane (PDMS). The overall stiffness of the microcapsules is governed by both the thickness and cross-link ratio of the polymer shell. Flowing suspensions of microcapsules through constricted spaces leads to transient blockage of fluid flow, thus altering the flow behavior. The ability to tune microcapsule mechanical properties enables the design of elastic microcapsules that can be tailored for desired flow behavior in a broad range of applications such as oil recovery, reactor feeding, red blood cell flow and chemical targeted delivery.
