Predictive functional control based on an adaptive fuzzy model of a hybrid semi-batch reactor

In this paper a new approach to the control of a nonlinear, time-varying process is proposed. It is based on a recursive version of the fuzzy identification method and predictive functional control. First, the recursive fuzzy identification method is derived, after which it is used in connection with fuzzy predictive functional control to construct an adaptive fuzzy predictive functional controller. The adaptive FPFC is then tested on a nonlinear, time-varying, semi-batch reactor process and compared with the standard FPFC, which uses non-adaptive fuzzy model. The simulation results are promising; they indicate that the control of time-varying, nonlinear processes with the FPFC can be improved with the use of an adaptive fuzzy model. An improvement in reference tracking and disturbance rejection can be observed, but the main advantage is the reduced number of switchings between hot and cold water. This is an important improvement in the case of real applications.     

The use of data-derived label hierarchies in multi-label classification

Instead of traditional (multi-class) learning approaches that assume label independency, multi-label learning approaches must deal with the existing label dependencies and relations. Many approaches try to model these dependencies in the process of learning and integrate them in the final predictive model, without making a clear difference between the learning process and the process of modeling the label dependencies. Also, the label relations incorporated in the learned model are not directly visible and can not be (re)used in conjunction with other learning approaches. In this paper, we investigate the use of label hierarchies in multi-label classification, constructed in a data-driven manner. We first consider flat label sets and construct label hierarchies from the label sets that appear in the annotations of the training data by using a hierarchical clustering approach. The obtained hierarchies are then used in conjunction with hierarchical multi-label classification (HMC) approaches (two local model approaches for HMC, based on SVMs and PCTs, and two global model approaches, based on PCTs for HMC and ensembles thereof). The experimental results reveal that the use of the data-derived label hierarchy can significantly improve the performance of single predictive models in multi-label classification as compared to the use of a flat label set, while this is not preserved for the ensemble models.     

A system for efficient motor learning using multimodal augmented feedback

Numerous studies have established that using various forms of augmented feedback improves human motor learning. In this paper, we present a system that enables real-time analysis of motion patterns and provides users with objective information on their performance of an executed set of motions. This information can be used to identify individual segments of improper motion early in the learning process, thus preventing improperly learned motion patterns that can be difficult to correct once fully learned. The primary purpose of the proposed system is to serve as a general tool in the research on impact of different feedback modalities on the process of motor learning, for example, in sports or rehabilitation. The key advantages of the system are high-speed and high-accuracy tracking, as well as its flexibility, as it supports various types of feedback (auditory and visual, concurrent or terminal). The practical application of the proposed system is demonstrated through the example of learning a golf swing.     

Shakedown analysis of circular plates using a yield criterion of the mean

Structural optimization based on the shakedown theory is a powerful and promising technique. However, due to the nonlinearities of physical materials and the number of variable loads in real structures, it is computationally complex and time-consuming. To simplify the occurring non-linear, non-convex optimization problems, the paper suggests reducing the number of yield conditions. The so-called a yield criterion of the mean (integral yield condition) is analysed and explained in detail, which allows taking into account one yield condition for the entire finite element instead of multiple point-wise conditions. This approach shows promising results in numerical application to the optimization of a circular plate, considering a possibility of employing the yield criteria of the mean or pointwise yield conditions in different areas of the plate in particular. The methods applied are based on the assumptions of perfect plasticity and small deformations.     

A Chamber for Testing the Release of Volatile Substances Secreted by Animals,Especially Mammals,as Exemplified by Substances Released by Rats in Response to Stress

Abstract

The success of the testing of volatile organic compounds emitted by animals is dependent on the creation of appropriate conditions for air sampling subsequently used to assay and identify the compounds. These conditions play a particularly important role in the investigation of pheromones, which are secreted in extremely low concentrations. The authors have not come across any previous work which offers constructional solutions, which would allow avoidance of contamination of the air samples containing volatile substances secreted by animals.

A constructional solution was developed, which provides optimal conditions for their sampling and isolation. Its main advantages are as follows: the exposure chamber (the chamber in which the animal is studied) is filled with synthetic air; the exposure chamber is separated from the atmospheric air with a synthetic air “jacket”; the exposure chamber has been constructed using materials which do not release chemicals and absorb them in trace quantities.     

Influence of Particle Size Distribution,Moisture Content,and Particle Shape on the Flow Properties of Bulk Solids

Abstract

There has been a great deal of research on characterising bulk solids. However, some of the characteristics, particularly the time‐dependent and random changes of properties, still remain insufficiently understood. The focus of this article is to study the influence of particle size, size distribution, moisture content, and particle shape on the unconfined yield strength of bulk solids. We present some interesting results about the influence of the particle size distribution on the unconfined yield strength of a bulk solid and a new method for determining the influence of particle shape on the unconfined yield strength of a bulk solid, which was made possible by the design and use of a novel attritor.     

Impact of computer training courses on reduction of loneliness of older people in Finland and Slovenia

Previous research has shown loneliness as a threat for the quality of life of older people; therefore the goal of the intervention in a quasi-experimental study was to evaluate and discuss the self-reported level of loneliness of older people in Finland and Slovenia before and after a computer intervention. Intervention in a quasi-experimental study was conducted among 58 older participants at the baseline (M = 72.4 years) and 45 older participants at the follow-up research study (M = 72.9 years). Inferential statistics showed a significant difference in the reduction of loneliness between the countries, and a decreased level of loneliness of older people after completing the computer training course. Although older people experience many age-related problems which may reduce their interest in learning information and communication technology (ICT) skills, it is important that they are computer-proficient, because computer engagement can reduce the level of loneliness of older people and in this way has a positive effect on their quality of life.     

On using planning poker for estimating user stories

While most studies in psychology and forecasting stress the possible hazards of group processes when predicting effort and schedule, agile software development methods recommend the use of a group estimation technique called planning poker for estimating the size of user stories and developing release and iteration plans. It is assumed that the group discussion through planning poker helps in identifying activities that individual estimators could overlook, thus providing more accurate estimates and reducing the over-optimism that is typical for expert judgment-based methods. In spite of the widespread use of agile methods, there is little empirical evidence regarding the accuracy of planning poker estimates. In order to fill this gap a study was conducted requiring 13 student teams to develop a Web-based student records information system. All teams were given the same set of user stories which had to be implemented in three Sprints. Each team estimated the stories using planning poker and the estimates provided by each team member during the first round were averaged to obtain the statistical combination for further comparison. In the same way the stories were estimated by a group of experts. The study revealed that students’ estimates were over-optimistic and that planning poker additionally increased the over-optimism. On the other hand, the experts’ estimates obtained through planning poker were much closer to actual effort spent and tended to be more accurate than the statistical combination of their individual estimates. The results indicate that the optimism bias caused by group discussion diminishes or even disappears as the expertise of the people involved in the group estimation process increases.