Spherical Flight Vehicle with single rotor using 4 control surface

Alexander Uskov, Bhuvana Sekar

The nascent technologies—smart serious games and smart gamification—potentially present an effective fusion of smart technology and smart systems on one side, and applications of computer game mechanics in “serious” areas and gamification of business processes on the other side. They can combine the features and advantages of both areas, and, as a result, provide the end users with non-existing functionality, features and advances. This chapter is aimed to analyze current status of serious games and gamified applications in industry, examine “smartness” maturity levels of smart objects and systems, classify main components and features and present conceptual design model of smart serious games and smart gamified applications, identify technical skills required for a design and development of smart serious games and smart gamification of business, research and development processes and simulations.

Science impacts everyone's world. With over 1,800 journals publishing articles from across science, technology and health, our mission is to share some of the stories that matter. Each month Atlas will showcase research that can (or already has) significantly impact people's lives around the world and we hope that bringing wider attention to this research will go some way to ensuring its successful implementation.

With so many worthy articles published the tough job of selecting a single article to be awarded "The Atlas" each month comes down to an Advisory Board. The winning research is presented alongside interviews, expert opinions, multimedia and much more on the Atlas website.

We aim to showcase some of the articles that can make a real difference and hope you'll find this to be a valuable resource.

The presence of energy hubs and the advancement in smart grid technologies have motivated system planners to deploy intelligent multicarrier energy systems entitled “smart energy hub” (S.E. Hub). In this paper, we model S.E. Hub, and propose a modern energy management technique in electricity and natural gas networks based on integrated demand side management (IDSM). In conventional studies, energy consumption is optimized from the perspective of each individual user without considering the interactions with each other. Here, the interaction among S.E. Hubs in IDSM program is formulated as a noncooperative game. The existence and uniqueness of a pure strategy Nash equilibrium (NE) is proved. Additionally, the strategies for each S.E. Hub are determined by proposing a distributed algorithm. We also address the IDSM game in a cloud computing (CC) framework to achieve efficient data processing and information management. Simulations are performed on a grid consisting of ten S.E. Hubs. We compare the CC framework with conventional data processing techniques to evaluate the efficiency of our proposed approach in determining NE. It is also shown that in the NE, the energy cost for each S.E. Hub and the peak-to-average ratio of the electricity demand decrease substantially.

This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning under uncertainty, sensor-based planning, visibility, decision-theoretic planning, game theory, information spaces, reinforcement learning, nonlinear systems, trajectory planning, nonholonomic planning, and kinodynamic planning.

Loesch, M.; Hufnagel, D. ; Steuer, S. ; Fabnacht, T. ; Schmeck, H.

A major component of the future Smart Grid is an adaptive demand side that allows to handle the fluctuating power supply based on renewable energies. In this paper, we present an evolutionary algorithm that allows for shifting electrical loads generated by heat pumps. Our approach is based on overheating the hot water storage in order to get a higher degree of freedom for scheduling. In our scenario, we assume time-variable price and load limitation signals as well as a prediction for local power generation from photovoltaic panels to incentivize the load shifting. Using these signals, we consider the future thermal demand to schedule the heat pump such that electricity costs are decreased. Our simulations show that heat pumps and hot water storages bear potential to shift loads over a time span of up to multiple hours, thus providing economical storage capacity. In doing so and based on electricity prices from the stock exchange, we were able to significantly decrease electricity costs for operating the heat pump.

Published in: Intelligent Energy and Power Systems (IEPS), 2014 IEEE International Conference on

OpenMarkov is a software tool for probabilistic graphical models (PGMs) developed by the Research Centre for Intelligent Decision-Support Systems of the UNED in Madrid, Spain.

It has been designed for:

• editing and evaluating several types of several types of PGMs, such as Bayesian networks, influence diagrams, factored Markov models, etc.;
• learning Bayesian networks from data interactively;
• cost-effectiveness analysis.

Elsevier introduces IPP, SNIP & SJR: A new perspective in journal metrics for researchers and publishers

Using hedge fund data as an example, this article demonstrates how MATLAB® can be used to automate the process of acquiring and analyzing fraud detection data.

Oliver Parson, is a research fellow in the Agents, Interaction and Complexity Group within Electronics and Computer Science at the University of Southampton. He is interested in investigating the ways in which machine learning techniques can be used to break down household energy consumption data into individual appliances, also known as Non-intrusive Appliance Load Monitoring (NIALM) or energy disaggregation.

Full-Function Web-Enabled Manuscript Submission and Tracking System for Peer Review

Cecati, C. ; Citro, C. ; Siano, P.

The integration of renewable energy systems (RESs) in smart grids (SGs) is a challenging task, mainly due to the intermittent and unpredictable nature of the sources, typically wind or sun. Another issue concerns the way to support the consumers' participation in the electricity market aiming at minimizing the costs of the global energy consumption. This paper proposes an energy management system (EMS) aiming at optimizing the SG's operation. The EMS behaves as a sort of aggregator of distributed energy resources allowing the SG to participate in the open market. By integrating demand side management (DSM) and active management schemes (AMS), it allows a better exploitation of renewable energy sources and a reduction of the customers' energy consumption costs with both economic and environmental benefits. It can also improve the grid resilience and flexibility through the active participation of distribution system operators (DSOs) and electricity supply/demand that, according to their preferences and costs, respond to real-time price signals using market processes. The efficiency of the proposed EMS is verified on a 23-bus 11-kV distribution network.

Sustainable Energy, IEEE Transactions on (Volume:2 , Issue: 4 ) - 2001

The tangent bug algorithm is actually the imroved version of Bug1 and Bug2 algorithms. Unlike these methods, tangent bug algorithm depends on the existence of a range sensor that is mounted on the point robot in the map. By only investigating the output ot this range sensor, and including the knowledge of the robot's current pose and goal's pose, the robot plans actions to reach to the goal.

This web page consists of information about the tangent bug algorithm and its implementation.

18/April/2007

In this report we discuss our implementation of a local path planning algorithm based on virtual potential field described in [1]. The algorithm uses virtual forces to avoid being trapped in a local minimum. Simulation and experiments are performed, and compared to the results presented in the paper. They show good performance and ability to avoid the local minimum problem in most of the cases.

Albert Y. Zomaya and Young Choon Lee, Chen Wang and Martin De Groot

The website of Bob Cromwell, with some nice articles about linux, UNIX and other stuff.