The Problem Based Learning (PBL)-Based Entrepreneurship Learning Model Development to Improve the Life Skills of the Teacher Training Students in Private Universities throughout Solo Raya

Purpose – This research aims at providing a PBL-based Entrepreneurship learning model to improve the student life skills in Private Faculties of Teacher Training and Educationin Solo Raya. Method – This research was a “research and development”. The research and development model consists of three steps: preliminary study, model development, and model testing. The research study stage employed a qualitative research; techniques of collecting data used were observation, interview, and content analysis and archive, while the data validation was done using data (source), method and theory triangulations, and informant review; data analysis was done using an interactive model of analysis. Findings – The implementation of life skills education in FKIP of UNISRI was not based on specific curriculum yet; the curriculum is integrated into all courses existing in the Study Program. The life skill content of each course is different but proportional and consistent with the characteristics of the course. Life skill education was given to the students in terms of the thinking and working skill, knowledge, and attitude the students to prepare themselves as independent members of society. Significance – The Problem Based Learning (PBL)-Based Entrepreneurship learning model development could improve the life skills of the private Teacher Training and Education Faculty’s Students throughout Solo Raya

Modeling Financial Time Series with Artificial Neural Networks

Financial time series convey the decisions and actions of a population of human actors over time. Econometric and regressive models have been developed in the past decades for analyzing these time series. More recently, biologically inspired artificial neural network models have been shown to overcome some of the main challenges of traditional techniques by better exploiting the non-linear, non-stationary, and oscillatory nature of noisy, chaotic human interactions. This review paper explores the options, benefits, and weaknesses of the various forms of artificial neural networks as compared with regression techniques in the field of financial time series analysis.CELEST, a National Science Foundation Science of Learning Center (SBE-0354378); SyNAPSE program of the Defense Advanced Research Project Agency (HR001109-03-0001

Reinforcement Learning: A Survey

This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the field and a broad selection of current work are summarized. Reinforcement learning is the problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment. The work described here has a resemblance to work in psychology, but differs considerably in the details and in the use of the word ``reinforcement.'' The paper discusses central issues of reinforcement learning, including trading off exploration and exploitation, establishing the foundations of the field via Markov decision theory, learning from delayed reinforcement, constructing empirical models to accelerate learning, making use of generalization and hierarchy, and coping with hidden state. It concludes with a survey of some implemented systems and an assessment of the practical utility of current methods for reinforcement learning.Comment: See http://www.jair.org/ for any accompanying file

Assessing framing of uncertainties in water management practice

Dealing with uncertainties in water management is an important issue and is one which will only increase in light of global changes, particularly climate change. So far, uncertainties in water management have mostly been assessed from a scientific point of view, and in quantitative terms. In this paper, we focus on the perspectives from water management practice, adopting a qualitative approach. We consider it important to know how uncertainties are framed in water management practice in order to develop practice relevant strategies for dealing with uncertainties. Framing refers to how people make sense of the world. With the aim of identifying what are important parameters for the framing of uncertainties in water management practice, in this paper we analyze uncertainty situations described by decision-makers in water management. The analysis builds on a series of ¿Uncertainty Dialogues¿ carried out within the NeWater project with water managers in the Rhine, Elbe and Guadiana basins in 2006. During these dialogues, representatives of these river basins were asked what uncertainties they encountered in their professional work life and how they confronted them. Analysing these dialogues we identified several important parameters of how uncertainties get framed. Our assumption is that making framing of uncertainty explicit for water managers will allow for better dealing with the respective uncertainty situations. Keywords Framing - Uncertainty - Water management practic

PID control system analysis, design, and technology

Designing and tuning a proportional-integral-derivative (PID) controller appears to be conceptually intuitive, but can be hard in practice, if multiple (and often conflicting) objectives such as short transient and high stability are to be achieved. Usually, initial designs obtained by all means need to be adjusted repeatedly through computer simulations until the closed-loop system performs or compromises as desired. This stimulates the development of "intelligent" tools that can assist engineers to achieve the best overall PID control for the entire operating envelope. This development has further led to the incorporation of some advanced tuning algorithms into PID hardware modules. Corresponding to these developments, this paper presents a modern overview of functionalities and tuning methods in patents, software packages and commercial hardware modules. It is seen that many PID variants have been developed in order to improve transient performance, but standardising and modularising PID control are desired, although challenging. The inclusion of system identification and "intelligent" techniques in software based PID systems helps automate the entire design and tuning process to a useful degree. This should also assist future development of "plug-and-play" PID controllers that are widely applicable and can be set up easily and operate optimally for enhanced productivity, improved quality and reduced maintenance requirements