The assembly line worker assignment and balancing problem with stochastic worker availability

Assembly lines can be employed successfully in sheltered work centres to better include persons with disabilities in the labour market as well as to improve production efficiency. The optimal assignment of a heterogeneous workforce is known as the assembly line worker assignment and balancing problem (ALWABP). These assembly lines are characterised not only by a heterogeneous workforce, but also by high levels of absenteeism, which makes it more difficult to obtain stable and efficient line balancing solutions. In this paper, an extension of the ALWABP to minimise the expected cycle time under uncertain worker availability is proposed. We model this problem as a two-stage mixed integer program, and propose local search heuristics for solving it. Computational experiments show that stochastic modelling can help to improve the line’s efficiency and that the proposed heuristics produce good results for instances of practical size.     

Dynamic fatigue behaviour of a steatite ceramic

Dynamic fatigue of a low dielectric loss steatite was investigated. To this end, the values of n and B, the so‐called subcritical crack growth (SCG) parameters were experimentally determined. The steatite exhibited the expected dynamic fatigue behaviour, so that the stress corrosion susceptibility parameter, n, of 24 was obtained. In addition, the material/environment parameter B, which is a constant for a given test environment, was also attained. These parameters are instrumental in predicting the lifetime of components under stress. When the applied load is such that the resulting strength equals half of the inert strength (σ_i), defined as the strength of a sample tested in an inert environment or at a fast stress rate, i.e. where no subcritical crack growth occurs, the time to failure (t_f) of the material was found to be ～140 h. Measurement of the fracture toughness of steatite is also of upmost importance and so it was determined using three test methods. A value of K_Ic = 1.91 ± 0.29 MPa m^1/2 was attained by the indentation fracture method through measurement of the cracks emanating from the Vickers indentation. This value is in good agreement with those determined using the K_Isc (surface crack in flexure) test method (2.21 ± 0.07 MPa m^1/2) and fractography analysis test method (2.00 ± 0.44 MPa m^1/2). Differences in test procedure and analysis causing the values from each test method to be different are discussed.     

Spatial and temporal variability of macrophyte cover and productivity in the eastern Amazon floodplain: A remote sensing approach

Herbaceous aquatic macrophytes cover extensive areas on the floodplains of the Amazon basin and are an important habitat and input of organic carbon. These communities have large intra- and inter-annual variability, and characterization of this variability is necessary to quantify the role of macrophytes in the ecology and biogeochemistry of the floodplain. A novel approach for mapping the temporal evolution of aquatic vegetation in the Amazon floodplain, which could be adapted to other spatially and temporally changing environments, is presented. Macrophyte cover varied seasonally and inter-annually, ranging between 104 and 198 km² for the floodplain examined (total area, 984 km²). The observed evolution of plant distribution indicated a spatial and temporal partition of macrophyte communities into short-lived and annual groups. A simulation of macrophyte net primary production (NPP) based on the mapping results indicated that at least 3% of NPP could be attributed to the short-lived communities. The present results suggest that significant changes in the macrophyte's contribution to carbon cycling in the Amazon floodplain could occur as a result of the predicted increase in frequency of drought years for the Amazon system due to climate change.     

Numerical study of the mixture formation process in a four-stroke GDI engine for two-wheel applications

Guidelines for managing the mixture formation process in a high-performance four-stroke Gasoline Direct Injection (GDI) engine for two-wheel applications are discussed, as derived from a multidimensional modelling of the in-cylinder processes. Gasoline adduction from a multi-hole injector is simulated by resorting to a properly developed model that accounts for the dependence of the initial droplets size distribution upon injection pressure. The model portability is preliminary demonstrated by comparison with experimental measurements carried out on sprays entering a confined vessel at controlled conditions.The simulation of different engine operating conditions highlights the capability to work under the so-called “mixed mode” boosting with spray guided mixture formation.     

A web-based formative assessment tool for Masters students: A pilot study

The use of web-based learning and assessment tools is growing in tertiary institutions around the world. To date, very few papers have reported the development and evaluation of a web-based formative assessment tool for postgraduate students. The aim of the present paper was to report on the development and evaluation of an online formative assessment tool for this student group. The web-based formative assessment tool was evaluated by a sample of undergraduate students, postgraduate students and academic staff within a psychology department in order to determine the suitability and sensitivity of the tool. The results of this pilot test suggest that the development of such a tool is both appropriate and feasible for Masters students studying psychology.     

A computational model for developing semantic web-based educational systems

Recently, some initiatives to start the so-called semantic web-based educational systems (SWBES) have emerged in the field of artificial intelligence in education (AIED). The main idea is to incorporate semantic web resources to the design of AIED systems aiming to update their architectures to provide more adaptability, robustness and richer learning environments. However, the construction of such systems is highly complex and faces several challenges in terms of software engineering and artificial intelligence aspects. This paper presents a computational model for developing SWBES focusing on the problem of how to make the development easier and more useful for both developers and authors. In order to illustrate the features of the proposed model, a case study is presented. Furthermore, a discussion about the results regarding the computational model construction is available.     

Skill Memory in Biped Locomotion

Robots must be able to adapt their motor behavior to unexpected situations in order to safely move among humans. A necessary step is to be able to predict failures, which result in behavior abnormalities and may cause irrecoverable damage to the robot and its surroundings, i.e. humans. In this paper we build a predictive model of sensor traces that enables early failure detection by means of a skill memory. Specifically, we propose an architecture based on a biped locomotion solution with improved robustness due to sensory feedback, and extend the concept of Associative Skill Memories (ASM) to periodic movements by introducing several mechanisms into the training workflow, such as linear interpolation and regression into a Dynamical Motion Primitive (DMP) system such that representation becomes time invariant and easily parameterizable. The failure detection mechanism applies statistical tests to determine the optimal operating conditions. Both training and failure testing were conducted on a DARwIn-OP inside a simulation environment to assess and validate the failure detection system proposed. Results show that the system performance in terms of the compromise between sensitivity and specificity is similar with and without the proposed mechanism, while achieving a significant data size reduction due to the periodic approach taken.     

Relational Learning with GPUs: Accelerating Rule Coverage

Relational learning algorithms mine complex databases for interesting patterns. Usually, the search space of patterns grows very quickly with the increase in data size, making it impractical to solve important problems. In this work we present the design of a relational learning system, that takes advantage of graphics processing units (GPUs) to perform the most time consuming function of the learner, rule coverage. To evaluate performance, we use four applications: a widely used relational learning benchmark for predicting carcinogenesis in rodents, an application in chemo-informatics, an application in opinion mining, and an application in mining health record data. We compare results using a single and multiple CPUs in a multicore host and using the GPU version. Results show that the GPU version of the learner is up to eight times faster than the best CPU version.     

Spatial data warehouses and spatial OLAP come towards the cloud: design and performance

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %.