Abstract
More than ever, the economic globalization is creating the need to increase business competitiveness. Lean manufacturing is a management philosophy oriented to the elimination of activities that do not create any type of value and are thus considered a waste. One of the main differences from other management philosophies is the shop-floor focus and the operators' involvement. Therefore, the training of all organization levels is crucial for the success of lean manufacturing. Universities should also participate actively in this process by developing students' lean management skills and promoting a better and faster integration of students into their future organizations. This paper proposes a single realistic manufacturing platform, involving production and assembly operations, to learn by playing many of the lean tools such as VSM, 5S, SMED, poke-yoke, line balance, TPM, Mizusumashi, plant layout, and JIT/kanban. This simulation game was built in tight cooperation with experienced lean companies under the international program "Lean Learning Academy,"1 and its main aim is to make bachelor and master courses in applied sciences more attractive by integrating classic lectures with a simulated production environment that could result in more motivated students and higher study yields. The simulation game results show that our approach is efficient in providing a realistic platform for the effective learning of lean principles, tools, and mindset, which can be easily included in course classes of less than two hours. © 2013 IEEE.

Abstract
In an increasingly competitive and globalized world, companies need effective training methodologies and tools for their employees. However, selecting the most suitable ones is not an easy task. It depends on the requirements of the target group (namely time restrictions), on the specificities of the contents, etc. This is typically the case for training in Lean, the waste elimination manufacturing philosophy. This paper presents and compares two different approaches to lean training methodologies and tools: a simulation game based on a single realistic manufacturing platform, involving production and assembly operations that allows learning by playing; and a digital game that helps understand lean tools. This paper shows that both tools have advantages in terms of trainee motivation and knowledge acquisition. Furthermore, they can be used in a complementary way, reinforcing the acquired knowledge. © 2013 IEEE.

Abstract

Abstract
A simulation teaching experiment to control a gantry crane system is proposed. The control is performed both in open-loop and closed-loop. The open-loop control is based on the Posicast feedforward technique and the closed-loop control uses a two-degrees of freedom configuration. Posicast control is used as a pre-filter outside the feedback loop to enhance the set-point tracking response and a PID controller is used in the feedback loop to deal with disturbance rejection. Students are required to use a gantry crane animation, to visualize its movement promoting a better perception and control techniques understanding. The experiment was performed by undergraduate feedback control students which provided learning results through a survey questionnaire.

Abstract
The characterization of heart rate variability (HRV) series has become important for clinical diagnosis. These series are non-stationary and exhibit long and short-range correlations. The non-parametric methodology detrended fluctuation analysis (DFA) has become widely used for the detection of these correlations. The standard procedure is to apply DFA to the RR series, estimating the desired scaling exponents. In this work we pursue an alternative approach which consists in applying DFA to the fractionally differenced RR series, Delta(RR)-R-d, where 0 < d < 1 is the long-range correlation parameter. Both methodologies are applied to 24 hour HRV series from the Noltisalis data base. We conclude that changes in HRV are better quantified by DFA scaling exponents calculated over fractionally differenced RR series than by the standard procedure. The results indicate that the scaling exponent corresponding to high frequencies obtained from Delta(RR)-R-d increases the discriminatory power among the groups: from 60% to 87% during the day period and 57% to 77% during the night period.

Abstract
The electronic storage of medical patient data is becoming a daily experience in most of the practices and hospitals worldwide. However, much of the available data is in free text form, a convenient way of expressing concepts and events but especially challenging if one wants to perform automatic searches, summarization, or statistical analyses. Information Extraction can relieve some of these problems by offering a semantically informed interpretation and abstraction of the texts. MedInX, the Medical Information eXtraction system presented in this chapter is designed to process textual clinical discharge records in order to perform automatic and accurate mapping of free text reports onto a structured representation. MedInX components are based on Natural Language Processing principles and provide several mechanisms to read, process, and utilize external resources, such as terminologies and ontologies. MedInX current practical applications include automatic code assignment and an audit system capable of systematically analyze the content and completeness of the clinical reports. Recent evaluation efforts on a set of authentic patient discharge letters indicate that the system performs with 95% precision and recall. © 2013, IGI Global.