Modeling of female human body shapes for apparel design based on cross mean sets

This paper is concerned with a method to build prototypes of human bodies that can be used for apparel design. One of the most important issues in the apparel development process is to define a sizing system to provide a good fitting for the majority of the population. Since anthropometric measures do not present the same linear growth with size in each dimension, it is very important to find a prototype that represents as accurately as possible each class in the sizing system. In this paper we propose a method based on the concept of random compact mean set to define prototypes in apparel design. From a cloud of 3D points obtained with a 3D scanner a solid that represents the human body is obtained. 2D cross sections of this solid are extracted at certain heights corresponding to key points of the body. These different cross-sections can be seen as a realization of a random compact set in the plane. A very popular definition on mean set is applied to each sample of 2D cross sections, and finally the prototype is obtained as the 3D reconstruction of these 2D mean sections. As a real example, the proposed methodology is applied to the 3D database obtained from a anthropometric survey of the Spanish female population conducted in this country in 2006.     

Human action recognition using multi-layer codebooks of key poses and atomic motions

Taking fully into consideration the fact that one human action can be intuitively considered as a sequence of key poses and atomic motions in a particular order, a human action recognition method using multi-layer codebooks of key poses and atomic motions is proposed in this paper. Inspired by the dynamics models of human joints, normalized relative orientations are computed as features for each limb of human body. In order to extract key poses and atomic motions precisely, feature sequences are segmented into pose feature segments and motion feature segments dynamically, based on the potential differences of feature sequences. Multi-layer codebooks of each human action are constructed with the key poses extracted from pose feature segments and the atomic motions extracted from motion feature segments associated with each two key poses. The multi-layer codebooks represent action patterns of each human action, which can be used to recognize human actions with the proposed pattern-matching method. Three classification methods are employed for action recognition based on the multi-layer codebooks. Two public action datasets, i.e., CAD-60 and MSRC-12 datasets, are used to demonstrate the advantages of the proposed method. The experimental results show that the proposed method can obtain a comparable or better performance compared with the state-of-the-art methods.     

The links between human error diversity and software diversity: Implications for fault diversity seeking

Software diversity is known to improve fault tolerance in N-version software systems by independent development. As the leading cause of software faults, human error is considered an important factor in diversity seeking. However, there is little scientific research focusing on how to seek software fault diversity based on human error mechanisms. A literature review was conducted to extract factors that may differentiate people with respect to human error-proneness. In addition, we constructed a conceptual model of the links between human error diversity and software diversity. An experiment was designed to validate the hypotheses, in the form of a programming contest, accompanied by a survey of cognitive styles and personality traits. One hundred ninety-two programs were submitted for the identical problem, and 70 surveys were collected. Code inspection revealed 23 faults, of which 10 were coincident faults. The results show that personality traits seems not effective predictors for fault diversity as a whole model, whereas cognitive styles and program measurements moderately account for the variation of fault density. The results also show causal relations between performance levels and coincident faults: coincident faults are unlikely to occur at skill-based performance level; the coincident faults introduced in rule-based performances show a high probability of occurrence, and the coincident faults introduced in knowledge-based performances are shaped by the content and formats of the task itself. Based on these results, we have proposed a model to seek software diversity and prevent coincident faults.     

Increasing X-ray image interpretation competency of cargo security screeners

X-ray screening of containers and unit load devices in the area of cargo shipping is becoming an essential and common feature at ports and airports all over the world. The detection of prohibited items in X-ray images is a challenging task for screening officers as they need to know which items are prohibited and what they look like in X-ray images. The main aim of this study was to investigate whether X-ray image interpretation competency of cargo security screeners can be increased by computer-based training. More specifically, effects of training were investigated by conducting tests before training started and after approximately three months of training. Moreover, it was examined whether viewing X-ray images in pseudo color would lead to a better detection performance compared to when X-ray images are shown in greyscale. Recurrent computer-based training resulted in large performance increases after three months. No significant difference in detection performance could be found for tests when using X-ray images in greyscale vs. pseudo color.     

The user in the loop: Enabling user participation for self-adaptive applications

Future computing systems must adjust to the user’s situations, habits, and intentions. Self-adaptive applications autonomously adapt to changing contexts without asking the user. However, the self-adaptive behaviour lacks of success if it does not correspond to the user’s personal interaction habits and intentions, particularly for complex scenarios with a high degree of user interaction. Concerning the interaction design, such adaptations can be irritating and distracting for the user if they do not match the current situation. In this article we provide a solution how to integrate the user in the self-adaptation feedback loop. The user will be able to influence the adaptation behaviour at run-time and in the long term by setting individual preferences. Consequently, we achieve a harmonisation between full application autonomy and user control. We implemented our generic concepts by extending an existing self-adaptation middleware with capabilities to respect the user’s application focus and interaction behaviour. A notification-based solution for user participation has been evaluated in a substantial user study with 62 participants. Although participants perceived much better control with our solution, the study made clear that notification design is specific for each adaptation type.     

Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach

This study intends to use a combination of fuzzy Analytic Hierarchy Process (AHP) and fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL) method in human resource for science and technology (HRST). Specifically, this study first uses AHP to evaluate the weighting for each criterion and then use DEMATEL method to establish contextual relationships among those criteria. We find out Infrastructure might be more critical since it is a cause and will directly influence human resource for science and technology performance. For human resource for science and technology (HRST), improving Infrastructure might be a better choice for the long period of time. Moreover, Education, R&D Expenses and Immediate output are more important second-tier criteria than Value, Cooperation, Labor Market, Human Capital and Intermediate output. Therefore, the improvement should be started with Infrastructure, particularly on identification of the Education, R&D Expenses and Immediate output.     

Fatty acid profile of milk from goats fed diets with different levels of conserved and fresh forages

Aim of the study was to evaluate the effect of different proportions of hay and fresh grass in goats’ diet on milk fatty acid profile. Nine Camosciata goats were fed a fixed amount of concentrate (30% of total diet) and different percentages (40% vs 30%, 50% vs 20% and 60% vs 10%) of hay and fresh grass, respectively. Diminishing amounts of fresh grass percentages in the diet led to significant increases of lauric, myristic and palmitic acids (P ≤ 0.001) and to significant decreases of C18:1 t6‐11, rumenic and α‐linolenic acids (P ≤ 0.001) in milk, thus determining a worsening of the health value of milk fat.     

A case for information theory-based modelling of human multitasking performance

Technological advances have led to increased prevalence of human multitasking. Traditionally, multitasking performance is measured for each individual task, utilising multiple performance metrics. Recently, the human operator informatic model (HOIM) has been developed as a quantitative model of human–machine interaction capable of measuring multitasking performance with a single metric. In this study, we investigated the performance effects of both a different number of tasks and five different task combinations while maintaining a constant level of overall difficulty. Results indicate that, at a constant difficulty level, neither number of tasks nor task combination significantly affects multitasking performance, indicating the reliability of input baud rate as a measure of system complexity. No task interaction effects were found among the different tasks. This study demonstrates the application of information theory for modelling of human multitasking performance and makes a case for the use of the HOIM in future studies of human information processing.     

Ergonomic evaluation of the musculoskeletal risks in a banana harvesting activity through qualitative and quantitative measures,with emphasis on motion capture (Xsens) and EMG

The objective of this study was to evaluate the risk of musculoskeletal injuries in a banana processing task. A sample of three workers were evaluated with the Nordic questionnaire as well as according to effort, discomfort and usability levels, hand grip dynamometry, inertial sensor motion capture (Xsens) and surface electromyography in the right arm. The workers had musculoskeletal complaints throughout the spine and hips, low effort and discomfort levels, and a satisfactory usability level. The hand grip strength values (dominant: 54.8 Kgf; non-dominant: 54.2 Kgf) were above the reference values for the Brazilian population. Regarding movement analysis, we identified risks related to cervical protrusion, forward and lateral trunk flexion, abduction and flexion in the shoulders, flexion, extension, radial and ulnar deviation in the wrists, as well as repetitive movements. Surface electromyography showed that the greatest demand during the task was on the extensor carpi radialis, although the trapezius and flexor carpi radialis showed a tendency toward fatigue. Thus, the set of evaluations showed that the tool used and worker adaptation to the position of the bunches, together with the repetitious movement, led to inadequate postures and musculoskeletal risks.Relevance to industryThe banana processing activity generates employment and income in several regions of the world and in Brazil. However, it is still rudimentary and may present risks to the worker's health. This study seeks to elucidate ergonomic risks through technological instrumentation in order to have a quantitative assessment of the ergonomic risks.