Innovation and application of ANN in Europe demonstrated by Kohonen maps

One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence

ASSESSMENT OF CONSUMERS POWER CONSUMPTION OPTIMIZATION BASED ON DEMAND SIDE MANAGEMENT

To ensure the functioning of the energy system, coordination and increase the efficiency of its parts need new control mechanisms. Generation, transmission and consumption of electricity needed control mechanisms that include integration of self-organizing power and heat supply systems, built on multi-agent principle. Also they must correspond intellectual basis, monitoring and accumulation. This includes effectiveness assessment of the state and analysis of technical, technological and organizational management mechanisms. One of the main parts is interaction principles of energy systems in accordance with European Community policy at various levels at liberalized electricity market. In most developed countries, demand management programs are widely used as a means of harmonizing the modes of generation and consumption in the power supply system. The main direct methods are set in the form of electricity tariffs. Indirect methods are set in the form of programs to manage electricity demand and the possibility of their application to manage electricity demand. Methods for estimating the unevenness of the daily schedule of electricity consumption and the factors influencing the technological environment are presented. The work aims at scientific and applied problem – finding methods of estimation and features of managing the demand for electricity. The use of the proposed estimation methods of electricity consumption influence non-uniformity on the level of power supplies system losses based on Frize QF power and optimization of consumers’ operation modes in the power supply system is considered. Approaches and optimization mechanisms of the daily electricity consumption on the example of a residential complex with the possibility of energy accumulation are offere

Design and Implementation of a State-Driven Operating System for Highly Reconfigurable Sensor Networks

Due to the low-cost and low-power requirement in an individual sensor node, the available computing resources turn out to be very limited like small memory footprint and irreplaceable battery power. Sensed data fusion might be needed before being transmitted as a tradeoff between procession and transmission in consideration of saving power consumption. Even worse, the application program needs to be complicated enough to be self-organizing and dynamically reconfigurable because changes in an operating environment continue even after deployment. State-driven operating system platform offers numerous benefits in this challenging situation. It provides a powerful way to accommodate complex reactive systems like diverse wireless sensor network applications. The memory usage can be bounded within a state transition table. The complicated issues like concurrency control and asynchronous event handling capabilities can be easily achieved in a well-defined behavior of state transition diagram. In this paper, we present an efficient and effective design of the state-driven operating system for wireless sensor nodes. We describe that the new platform can operate in an extremely resource constrained situation while providing the desired concurrency, reactivity, and reconfigurability. We also compare the executing results after comparing some benchmark test results with those on TinyOS

Pseudorotaxane strategies for guiding self-assembly and the application of molecular machinery in photoelectrochemical devices

Over the years, chemists have become masters of covalent bond formation, demonstrated by the ability to synthesize complicated natural products and their derivatives. Conversely, control of structures beyond the molecule has not yet reached the same level of sophistication. Supramolecular organization is ubiquitous in biology and non-covalent interactions are extensively applied to (pre-)organize the individual compositional elements to achieve optimal operation as emergent functionality. Understanding (supra)molecular organization could enable the creation of novel types chemical systems with new functions. This thesis aims to explore the use of supramolecular organization by using pseudorotaxane strategies to create functional chemical systems. As both fundamental understanding and application are investigated in this thesis, the work is divided into two parts. Part A demonstrates two examples of pathway engineering for non-covalent synthesis by employing a pseudorotaxane strategy. In one example the ring is used as a catalyst to guide self-assembly, while in the second example the ring binding impedes on the possible outcomes of multi-ligand architectures, and thereby organizing the self-assembled structures. In part B the central topic is supramolecular organization to improve charge separation in artificial photosynthesis. Photoelectrochemical devices benefit from implementing supramolecular organization promoting the forward electron propagation, eventually leading to enhanced device performance. Using this bio-inspired approach, three different types of molecular machines were designed and applied to address electron-hole recombination issues found in p-DSSCs. In both parts of the thesis, the power of the non-covalent bond is demonstrated, gaining insight in possible applications and underlying concepts of chemistry beyond the molecule

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Modular Self-Reconfigurable Robot Systems

The field of modular self-reconfigurable robotic systems addresses the design, fabrication, motion planning, and control of autonomous kinematic machines with variable morphology. Modular self-reconfigurable systems have the promise of making significant technological advances to the field of robotics in general. Their promise of high versatility, high value, and high robustness may lead to a radical change in automation. Currently, a number of researchers have been addressing many of the challenges. While some progress has been made, it is clear that many challenges still exist. By illustrating several of the outstanding issues as grand challenges that have been collaboratively written by a large number of researchers in this field, this article has shown several of the key directions for the future of this growing fiel