Force Control Strategy of Five-Digit Precision Grasping With Aligned and Unaligned Configurations

Objective To investigate the digit force control during a five-digit precision grasp in aligned (AG) and unaligned grasping (UG) configurations. Background The effects of various cylindrical handles for tools on power grasp performance have been previously investigated. However, there is little information on force control strategy of precision grasp to fit various grasping configurations. Method Twenty healthy young adults were recruited to perform a lift-hold-lower task. The AG and UG configurations on a cylindrical simulator with force transducers were adjusted for each individual. The applied force and moment, the force variability during holding, and force correlations between thumb and each finger were measured. Result No differences in applied force, force correlation, repeatability, and variability were found between configurations. However, the moments applied in UG were significantly larger than those in AG. Conclusion The force control during precision grasp did not change significantly across AG and UG except for the digit moment. The simulator is controlled efficiently with large moment during UG, which is thus the optimal configuration for precision grasping with a cylindrical handle. Further research should consider the effects of task type and handle design on force control, especially for individuals with hand disorders. Application To design the handle of specific tool, one should consider the appropriate configuration according to the task requirements of precision grasping to reduce the risk of accumulating extra loads on digits with a cylindrical handle.

An ontology-based approach to the analysis of the acid-base state of patients at operative measures

Researchers working in various domains are focusing on extracting information from data sets by data mining techniques. However, data mining is a complicated task, including multiple complex processes, so that it is unfriendly to non-computer researchers. Due to the lack of experience, they cannot design suitable workflows that lead to satisfactory results. This article proposes an ontology-based approach to help users choose appropriate data mining techniques for analyzing domain data. By merging with domain ontology and extracting the corresponding sub-ontology based on the task requirements, an ontology oriented to a specific domain is generated that can be used for algorithm selection. Users can query for suitable algorithms according to the current data characteristics and task requirements step by step. We build a workflow to analyze the Acid-Base State of patients at operative measures based on the proposed approach and obtain appropriate conclusions.

Interpreting Developmental Surface Dyslexia within a Comorbidity Perspective

Recent evidence underlines the importance of seeing learning disorders in terms of their partial association (comorbidity). The present concept paper presents a model of reading that aims to account for performance on a naturalistic reading task within a comorbidity perspective. The model capitalizes on the distinction between three independent levels of analysis: competence, performance, and acquisition: Competence denotes the ability to master orthographic–phonological binding skills; performance refers to the ability to read following specific task requirements, such as scanning the text from left to right. Both competence and performance are acquired through practice. Practice is also essential for the consolidation of item-specific memory traces (or instances), a process which favors automatic processing. It is proposed that this perspective might help in understanding surface dyslexia, a reading profile that has provoked a prolonged debate among advocates of traditional models of reading. The proposed reading model proposes that surface dyslexia is due to a defective ability to consolidate specific traces or instances. In this vein, it is a “real” deficit, in the sense that it is not due to an artifact (such as limited exposure to print); however, as it is a cross-domain defect extending to other learning behaviors, such as spelling and math, it does not represent a difficulty specific to reading. Recent evidence providing initial support for this hypothesis is provided. Overall, it is proposed that viewing reading in a comorbidity perspective might help better understand surface dyslexia and might encourage research on the association between surface dyslexia and other learning disorders.

Skill set issues in aircraft maintenance from industrial revolution 4.0 context: A document analytics survey

BACKGROUND: Aircraft maintenance and repair are critical tasks in the aviation industry for improved aircraft service and safety. Many articles and reports describe personnel factor and skill issues contribute to many aircraft incidents. Aircraft maintenance personnel needs to level up their skill set to match with task requirements in the setting of Industry Revolution 4.0. OBJECTIVE: The aim of this paper is to investigate document set that describe human errors and skill mismatch as a human factor in aircraft incidents and problems. It also discusses on the findings and management of the aircraft maintenance skill issues. METHODS: The study uses a document analytics tool to assess a set of online articles that discuss aircraft maintenance incidents and skill mismatch issues. The experiment is divided into four (4) modules: I collection of online articles and reports, (ii) document pre-processing, (iii) text analytics, and (iv) visualisation. RESULTS: The experiment’s results show that the majority of documents discuss aircraft maintenance, skill mismatch, and training gaps. CONCLUSION: We can conclude that the document dataset primarily discusses aircraft maintenance and skill set issues using the document analytics. Consequently, the management of aircraft maintenance workforce skill set issues by having initiatives for upskilling and reskilling Furthermore, firms should foster a culture of continuous learning and develop a mindset among their employees that allows them to adapt to new technologies and information in aircraft maintenance.

Intelligent recommendation algorithm of mobile application crowdsourcing test based on deep learning

As the functions of mobile applications become more and more complex, the crowdsourcing testing puts higher demands on the professional skills of testers. Therefore, it is an important factor to ensure test quality how to effectively match test task requirements with test personnel's skill level and achieve accurate crowdsourcing test task recommendation. This paper proposes a crowdsourcing test task recommendation algorithm for mobile applications based on deep learning. Firstly, feature analysis is carried out for testing tasks and testers, and feature systems are designed respectively. Second, the resulting characteristic data is used as input data for the Stacked Marginalized Denoising Autoencoder (SMDA). The deep feature data learned from SMDA are combined as the input of Deep Neural Networks (DNN). Finally, the learning ability of DNN is used for prediction. Experimental results show that the proposed algorithm has obvious advantages in both performance and training time compared with CDL and AUTOSVD ++, which verifies the effectiveness of the proposed algorithm. The proposed algorithm can recommend testing tasks to appropriate testers and improve the precision of the algorithm.

From Neural Command to Robotic Use: The Role of Symmetry/Asymmetry in Postural and Locomotor Activities

This article deepens a reflection on why and how symmetry/asymmetry affects the motor and postural behavior from the neural source, uterine development, child maturation, and how the notion of symmetry/asymmetry has been applied to walking robot design and control. The concepts of morphology and tensegrity are also presented to illustrate how the biological structures have been used in both sciences and arts. The development of the brain and the neuro-fascia-musculoskeletal system seems to be quite symmetric from the beginning of life through to complete maturity. The neural sources of movements (i.e., central pattern generators) are able to produce both symmetric or asymmetric responses to accommodate to environmental constraints and task requirements. Despite the fact that the human development is mainly symmetric, asymmetries already regulate neurological and physiological development. Laterality and sports training could affect natural musculoskeletal symmetry. The plasticity and flexibility of the nervous system allows the abilities to adapt and compensate for environmental constraints and musculoskeletal asymmetries in order to optimize the postural and movement control. For designing humanoid walking robots, symmetry approaches have been mainly used to reduce the complexity of the online calculation. Applications in neurological retraining and rehabilitation should also be considered.

ALGORITHMIC APPROACH TO QUANTITATIVE PROBLEM-SOLVING IN CHEMISTRY

Examining students' inclinations to use algorithms and rules to solve a task was a fruitful area of research in chemical education in the last four decades. This research aimed to examine whether students read the task request carefully, considering its meaningfulness, or they approach it mechanically, applying a set of algorithms by default. The research sample consisted of students majoring in chemistry teaching at the University of Novi Sad, Faculty of Sciences who were in their final year of bachelor studies. The study was conducted during two academic years. The main instrument consisted of five quantitative problems, and each of the problems contained deceptive information that made the calculation nonsensical. The results revealed that most students applied an algorithmic approach without paying attention to the meaningfulness of the task requirements. Additionally, it has been shown that students rely heavily on memorizing formulas without a proper understanding of underlying concepts. Keywords: algorithms, conceptual understanding, quantitative problems

Variability in the Center of Mass State During Initiation of Accurate Forward Step Aimed at Targets of Different Sizes

Motor control for forward step initiation begins with anticipatory postural adjustments (APAs). During APAs, the central nervous system controls the center of pressure (CoP) to generate an appropriate center of mass (CoM) position and velocity for various task requirements. In this study, we investigated the effect of required stepping accuracy on the CoM and CoP parameters during APA for a step initiation task. Sixteen healthy young participants stepped forward onto the targets on the ground as soon as and as fast as possible in response to visual stimuli. Two target sizes (small: 2 cm square and large: 10 cm square) and two target distances (short: 20% and long: 40% of the body height) were tested. CoP displacement during the APA and the CoM position, velocity, and extrapolated CoM at the timing of the takeoff of the lead leg were compared among the conditions. In the small condition, comparing with the large condition, the CoM position was set closer to the stance limb side during the APA, which was confirmed by the location of the extrapolated center of mass at the instance of the takeoff of the lead leg [small: 0.09 ± 0.01 m, large: 0.06 ± 0.01 m, mean and standard deviation, F(1, 15) = 96.46, p < 0.001, η2 = 0.87]. The variability in the mediolateral extrapolated center of mass location was smaller in the small target condition than large target condition when the target distance was long [small: 0.010 ± 0.002 m, large: 0.013 ± 0.004 m, t(15) = 3.8, p = 0.002, d = 0.96]. These findings showed that in the step initiation task, the CoM state and its variability were task-relevantly determined during the APA in accordance with the required stepping accuracy.

Gaze control during reaching is flexibly modulated to optimize task outcome

When reaching for an object with the hand, the gaze is usually directed at the target. In a laboratory setting, fixation is strongly maintained at the reach target until the reaching is completed, a phenomenon known as "gaze-anchoring". While conventional accounts of such tight eye-hand coordination have often emphasized the internal synergetic linkage between both motor systems, more recent optimal control theories regard motor coordination as the adaptive solution to task requirements. We here investigated to what degree gaze control during reaching is modulated by task demands. We adopted a gaze-anchoring paradigm in which participants had to reach for a target location. During the reach, they additionally had to make a saccadic eye movement to a salient visual cue presented at locations other than the target. We manipulated the task demands by independently changing reward contingencies for saccade reaction time (RT) and reaching accuracy. On average, both saccade RTs and reach error varied systematically with reward condition, with reach accuracy improving when the saccade was delayed. The distribution of the saccade RTs showed two types of eye movements: fast saccades with short RTs, and voluntary saccade with longer RTs. Increased reward for high reach accuracy reduced the probability of reflexive fast saccades, but left their latency unchanged. The results suggest that gaze-anchoring acts through a suppression of fast saccades, a mechanism that can be adaptively adjusted to the current task demands.