bluuebunny/crossref_metadata_2025_split huggingface dataset:
Water: Nature's Amazing Reusable Resource
Authors: Macpherson Linda 
Published: March 2010

The notion of reused water can evoke negative images. When further complicated by the public's lack of understanding of the water cycle, coupled with a widespread skepticism and distrust of technology, a much needed water supply strategy can easily become doomed.
Much of the attitudinal landscape is beyond the control of water managers but the problem can be exacerbated by the vocabulary and images typically used to define water and wastewater treatment. The compartmentalization of water supply and wastewater treatment into different organizations has resulted in poor understanding of water cycle management which has a particularly negative impact on water reuse, which is made to sound unusual - and people have a tendency to fear things that are out of the ordinary and seemingly strange. The water industry has also disproportionately focused on the history of the water rather than its treatment and ultimate safety for its intended use.
This presentation describes an approach to work through these issues in a manner that encompasses rational thought as well as emotion and feelings and shows that when the general public are given the opportunity to reframe their understanding of water and to have a more realistic view of water quality, they are drawn to different conclusions. If a lack of knowledge by the public about water is the single largest barrier to sustainable water management, then it is essential we do a better job of using language and imagery to create a deeper understanding of the water cycle and water treatment.
Singapore's Marina Barrage - Changing Mindsets in Urban Solutions
Authors: Harley Brendan M. , Guan Yap Kheng 
Published: March 2010

Singapore's water resources system is a strong illustration of the value of an integrated water resources management in urban enviroments. Today, urban water resources planning and environmental engineering are essential partners in the planning of tomorrow's urban environments - and not just as passive projects unnoticed by the public.
In Singapore we can see the specific evolution from the separate development of water catchments and the control of monsoon flooding to the integrated water management strategy as exemplified today in the Marina Barrage. The multi-purpose project boosts Singapore's water supply by creating its first reservoir in the city, helps flood control and enhances the living environment of the city.
Marina Barrage presented many interesting challenges in the development of a project whose impact was designed to far transcend the normal functional aspect of a large public works project.
This paper will present the many potential public uses that were considered in the planning for the final facility. The motivation is that the 3P (people, public and private) sectors play an important part in sustaining water resources. Instead of designing the Marina Barrage as a conventional functional facility accessible only to operational staff, the project breaks new ground in taking an unconventional design approach. The facility was designed as an open facility to engage and inspire the public to care for water. Features for public education, lifestyle attraction, eating experiences, options for families to relax, play areas for children, attractions for overseas visitors, spaces for dedicated conferences and many more were considered. A multi-functional team of interior designers, landscape architects, researchers, art specialists, lighting specialists, environmentalists, etc was assembled and met continually as the design evolved. These evolving goals had to be integrated into the overall functional characteristics of the barrage.
The resulting project is a world-class example of how a project initially conceived for water resources functional purpose can evolve not just into an iconic structure but one whose multi-functional capabilities have attracted huge attention from tourists and the people of Singapore. This is evidenced by more than 250,000 people visiting the facility in its first 6 months of operations, and the many families who spend relaxing time enjoying the various spaces at the Barrage.
The evolution of the Marina Barrage in design and operation can act as a lesson for other cities considering similar large flood control or water supply projects. The success of the Marina Barrage's 3P mission indicates how for a relatively little increase in cost these facilities can play a major role in enhancing urban lifestyle in sustainable cities.
Optiflux® RO design with center port pressure vessels for water treatment plant Dinxperlo, The Netherlands
Authors: Jong Ron C.M. , Kalf Marc J. , van der Meer Walter G.J. 
Published: March 2010

Recent commissioned Vitens NF and RO treatment plants are provided with the Optiflux® stack configuration. Aim of the Optiflux® concept is to optimize the permeate flow in RO/NF plants by minimizing hydraulic pressure losses and the osmotic pressure difference across the membrane surface. An increase in permeate productivity of 20% can be achieved, for both NF and RO membrane filtration systems, by lowering the number of membrane modules per pressure vessel to three, which leads to lower hydraulic pressure losses.
In one pressure vessel of 6 elements with 3 elements in each side and a center port in the middle; the feed water flows in the two directions (each side of the pressure vessel) and passes through the 3 elements of each side and the retentate is collected in the center port and feeds the second stage with the same principal. The permeate flows via the center tube of the spiral wound membranes and is collected in the permeate tank. The first full scale plant of 320 m3/h based on this concept is already commissioned at the 20th November 2006 at Vitens drinking water treatment plant Dinxperlo in The Netherlands.
Silica Scaling on Reverse Osmosis Membranes - Investigation and New Test Methods
Authors: Hater Wolfgang , Kolk Christian zum , Dupoiron Claire , Braun Gerd , Harrer Timo , Götz Thomas 
Published: March 2010

Scaling calculations are usually only based on the silicate concentration in the feed water, because suitable test methods for the interaction of silica with other ions are missing. As the contents of the other ions, i.e. above all calcium and magnesium are not considered, this method is incorrect and can lead to substantial problems.
In this paper first the results of laboratory experiments investigating the influence of different cations on the behaviour of supersaturated solutions of silica in different test waters are discussed. Subsequently, the results of the new membrane-based test method considering the influence of Ca2+ and Mg2+, the pH-value and the addition of antiscalants are discussed.
Different methods of analysis made it possible to distinguish three groups of silicates: ‘monomeric’, ‘polymeric’ and ‘filterable’. Ca2+ and Mg2+-ions have a strong influence on the formation of filterable silicate and on the kinetics of the formation of the different silicate species.
The ‘polymeric silica’ is mainly responsible for the membrane scaling, and the kinetic of its formation is strongly influenced by the cations and the pH-Value.
The antiscalant Osmotech 1309 makes it possible to operate the plant at significantly higher recovery rates, resp. at higher SiO2-concentrations.
A Formalism for Learning from Demonstration*
Authors: Billing Erik A. , Hellström Thomas 
Published: March 2010

Abstract
The paper describes and formalizes the concepts and assumptions involved in Learning from Demonstration (LFD), a common learning technique used in robotics. LFD-related concepts like goal, generalization, and repetition are here defined, analyzed, and put into context. Robot behaviors are described in terms of trajectories through information spaces and learning is formulated as mappings between some of these spaces. Finally, behavior primitives are introduced as one example of good bias in learning, dividing the learning process into the three stages of behavior segmentation, behavior recognition, and behavior coordination. The formalism is exemplified through a sequence learning task where a robot equipped with a gripper arm is to move objects to specific areas. The introduced concepts are illustrated with special focus on how bias of various kinds can be used to enable learning from a single demonstration, and how ambiguities in demonstrations can be identified and handled.
Exploring Parameter Space in Reinforcement Learning
Authors: Rückstieß Thomas , Sehnke Frank , Schaul Tom , Wierstra Daan , Sun Yi , Schmidhuber Jürgen 
Published: March 2010

Abstract
This paper discusses parameter-based exploration methods for reinforcement learning. Parameter-based methods perturb parameters of a general function approximator directly, rather than adding noise to the resulting actions. Parameter-based exploration unifies reinforcement learning and black-box optimization, and has several advantages over action perturbation. We review two recent parameter-exploring algorithms: Natural Evolution Strategies and Policy Gradients with Parameter-Based Exploration. Both outperform state-of-the-art algorithms in several complex high-dimensional tasks commonly found in robot control. Furthermore, we describe how a novel exploration method, State-Dependent Exploration, can modify existing algorithms to mimic exploration in parameter space.
Soft missing-feature mask generation for Robot Audition
Authors: Takahashi Toru , Nakadai Kazuhiro , Komatani Kazunori , Ogata Tetsuya , Okuno Hiroshi G. 
Published: March 2010

Abstract
This paper describes an improvement in automatic speech recognition (ASR) for robot audition by introducing Missing Feature Theory (MFT) based on soft missing feature masks (MFM) to realize natural human-robot interaction. In an everyday environment, a robot’s microphones capture various sounds besides the user’s utterances. Although sound-source separation is an effective way to enhance the user’s utterances, it inevitably produces errors due to reflection and reverberation. MFT is able to cope with these errors. First, MFMs are generated based on the reliability of time-frequency components. Then ASR weighs the time-frequency components according to the MFMs. We propose a new method to automatically generate soft MFMs, consisting of continuous values from 0 to 1 based on a sigmoid function. The proposed MFM generation was implemented for HRP-2 using HARK, our open-sourced robot audition software. Preliminary results show that the soft MFM outperformed a hard (binary) MFM in recognizing three simultaneous utterances. In a human-robot interaction task, the interval limitations between two adjacent loudspeakers were reduced from 60 degrees to 30 degrees by using soft MFMs.
The NSB control: a behavior-based approach for multi-robot systems
Authors: Antonelli Gianluca , Arrichiello Filippo , Chiaverini Stefano 
Published: March 2010

Abstract
The paper presents an overview on the use of a behavior-based approach, namely the Null-Space-based Behavioral (NSB) approach, to control multi-robot systems in a wide application domain. The NSB approach has been recently developed to control the motion of generic robotic systems; it uses a projection mechanism to combine the multiple, prioritized, behaviors that compose the robotic mission so that the lower priority behaviors do not effect the higher priority ones. In this paper we describe how the NSB approach has been used to control different multi-robot systems (e.g., composed of wheeled and marine robots) to achieve missions such as formation control, entrapping/escorting of targets, control of mobile ad-hoc networks, flocking, border patrol and cooperative caging.
Abstract intelligence and cognitive robots
Authors: Wang Yingxu 
Published: March 2010

Abstract
Abstract intelligence is the human enquiry of both natural and artificial intelligence at the neural, cognitive, functional, and logical levels reductively from the bottom up. According to the abstract intelligence theory, a cognitive robot is an autonomous robot that is capable of thought, perception, and learning based on the three-level computational intelligence known as the imperative, autonomic, and cognitive intelligence. This paper presents the theoretical foundations of cognitive robots based on the latest advances in abstract intelligence, cognitive informatics, and denotational mathematics. A formal model of intelligence known as the Generic Abstract Intelligence Mode (GAIM) is developed, which provides a foundation to explain the mechanisms of advanced natural intelligence such as thinking, learning, and inference. A set of denotational mathematics is introduced for rigorously modeling and manipulating the behaviors of cognitive robots. A case study on applications of a denotational mathematics, visual semantic algebra (VSA), is presented in architectural and behavioral modeling of cognitive robots based on the theory of abstract intelligence.
Hybridisation of Evolutionary Algorithms for Solving Multi-Objective Simulation Optimisation Problems
Authors: Napalkova Liana 
Published: March 2010

Hybridisation of Evolutionary Algorithms for Solving Multi-Objective Simulation Optimisation ProblemsThe paper presents a taxonomic analysis of existing hybrid multi-objective evolutionary algorithms aimed at solving multi-objective simulation optimisation problems. For that, the properties of evolutionary algorithms and the requirements made to solving the problem considered are determined. Finally, a combination of the properties, which allows one to increase the approximation accuracy of the Pareto-optimal front at relatively low computational costs, is revealed.
Inventory Management in Multi Echelon Supply Chain using Sample Average Approximation
Authors: Soshko Oksana 
Published: March 2010

Inventory Management in Multi Echelon Supply Chain using Sample Average ApproximationAn optimization model of multiechelon supply chain is presented in this paper. The decisions to be made are the amount of beer to be ordered in every echelon of supply chain in each echelon over the time horizon of one year. Since demand of the end customer is stochastic and presented by means of scenarios, the problem is solved by using sample average approximation method. This method uses only a subset of the scenarios, randomly sampled according to the distribution over scenarios, to represent the full scenario space. An important theoretical justification for this method is that as the number of scenarios sampled increases, the solution to the approximate problem converges to an optimal solution in the expected sense. The computational results are presented for two cases. First target level is chosen as a decision variable and then order size is chosen as a decision variable of the problem. The target level strategy is based on making inventory for each echelon; in its turn order strategy is based on determination of optimal order quantity, which is independent from scenarios. However target level strategy provides high service at low cost, but it offers less reality under uncertain demand than order strategy. Practical experiments on finding the optimal SAA parameters are presented in the paper and as well as the analysis of their impact on solution quality.
A Multilayered Self-Learning Spiking Neural Network and its Learning Algorithm Based on ‘Winner-Takes-More’ Rule in Hierarchical Clustering
Authors: Bodyanskiy Yevgeniy , Dolotov Artem 
Published: March 2010

A Multilayered Self-Learning Spiking Neural Network and its Learning Algorithm Based on ‘Winner-Takes-More’ Rule in Hierarchical ClusteringThis paper introduces architecture of multilayered selflearning spiking neural network for hierarchical data clustering. It consists of the layer of population coding and several layers of spiking neurons. Contrary to originally suggested multilayered spiking neural network, the proposed one does not require a separate learning algorithm for lateral connections. Irregular clusters detecting capability is achieved by improving the temporal Hebbian learning algorithm. It is generalized by replacing ‘Winner-Takes-All’ rule with ‘Winner-Takes-More’ one. It is shown that the layer of receptive neurons can be treated as a fuzzification layer where pool of receptive neurons is a linguistic variable, and receptive neuron within a pool is a linguistic term. The network architecture is designed in terms of control systems theory. Using the Laplace transform notion, spiking neuron synapse is presented as a second-order critically damped response unit. Spiking neuron soma is modeled on the basis of bang-bang control systems theory as a threshold detection system. Simulation experiment confirms that the proposed architecture is effective in detecting irregular clusters.
A Study on the Behaviour of the Algorithm for Finding Relevant Attributes and Membership Functions
Authors: Gasparoviča Madara , Aleksejeva Ludmila 
Published: March 2010

A Study on the Behaviour of the Algorithm for Finding Relevant Attributes and Membership FunctionsOne of the most recent approaches in machine learning is fuzzy rules usage for solving classification problems. This paper describes the algorithm for finding relevant attributes and searching for membership functions. Experimental results are used to clarify - which data sets can be used to automatically gain primary membership functions from primary data. This quality - gaining of membership functions - is one of the pros of the algorithm, because it eases resolution of classification task. The ability to use it with fuzzy data is one more merit. As a result, there are obtained reliable fuzzy classification rules to separate classes. By reconstructing primary membership functions also the number of IF-THEN rules gained from decision tables is reduced up to three times. Four experiments are conducted with different training and testing data set sizes. Conclusions are made about the optimal size of the training and testing data set that is necessary for achieving better results as well as about the data this algorithm is appropriate for. Finally, possible directions for further research are outlined.
Perceptron Architecture Ensuring Pattern Description Compactness
Authors: Jakovlevs Sergejs 
Published: March 2010

Perceptron Architecture Ensuring Pattern Description CompactnessThis paper examines conditions a neural network has to meet in order to ensure the formation of a space of features satisfying the compactness hypothesis. The formulation of compactness hypothesis is defined in more detail as applied to neural networks. It is shown that despite the fact that the first layer of connections is formed randomly, the presence of more than 30 elements in the middle network layer guarantees a 100% probability that the G-matrix of the perceptron will not be special. It means that under additional mathematical calculations made by Rosenblatt, the perceptron will with guaranty form a space of features that could be then linearly divided. Indeed, Cover's theorem only says that separation probability increases when the initial space is transformed into a higher dimensional space in the non-linear case. It however does not point when this probability is 100%. In the Rosenblatt's perceptron, the non-linear transformation is carried out in the first layer which is generated randomly. The paper provides practical conditions under which the probability is very close to 100%. For comparison, in the Rumelhart's multilayer perceptron this kind of analysis is not performed.
Practice of Web Data Mining Methods Application
Authors: Osipov Pavel , Borisov Arkady 
Published: March 2010

Practice of Web Data Mining Methods ApplicationRecent growth of information on the Internet imposes high demands on the effectiveness of processing algorithms. This paper discusses some algorithms from the field of Web Data Mining which have proved effective in many existing applications. The paper is divided into two logical parts; the first part provides a theoretical description of the algorithms, but the second one contains examples of their successful use to solve real problems. Search algorithms of vague duplicates of documents are currently actively used by all the leading search engines in the world. The paper describes the following algorithms: shingles, signature methods and image-based algorithms. Such methods of classification as a method of fuzzy clustering to-medium (Fuzzy cmeans/ FCM clustering) and clustering by ant colony (Standard Ant Clustering Algorithm SACA) are considered. In conclusion, the experience of the successful application of fuzzy clustering in conjunction with the software toolkit DataEngine to improve the efficiency of the bank "BCI Bank" is described as well as the sharing of the ant colony clustering method in conjunction with linear genetic programming to meet the increasing efficiency of predicting the load on the servers of high load Internet portal Monash Institut.
Usage of Ontologies in Systems of Data Exchange
Authors: Osipov Pavel , Borisov Arkady 
Published: March 2010

Usage of Ontologies in Systems of Data Exchange
This paper describes the methods and techniques used to effectively extract knowledge from large volumes of heterogeneous data. Also, methods to structure the raw data by the automatic classification using ontology are discussed. In the first part of the article the basic technologies to realize the Semantic WEB are described. Much attention is paid to the ontology, as the major concepts that structure information on a very high level. The second part examines AVT-DTL algorithm proposed by Jun Zhang which allows one to automatically create classifiers according to the available raw, potentially incomplete data. The considered algorithm uses a new concept of floating levels of ontology; the results of the tests show that it outperforms the best existing algorithms for creating classifiers.
Functional Management of Economy
Authors: Ratnieks Aloizs 
Published: March 2010

Functional Management of Economy
This paper discusses the unknown before property of adapting systems which consists in that the adapting system may be operated without any information about its condition. It is necessary to know only some characteristics of its elements. It was found, however, that the economic methods of management have limited possibilities, it is impossible to regulate with their help all those parameters which are not involved in the process of exchange. Another, more universal, economic management method is provided. The economic method of management discussed in the paper enables one to separate the management of economy from labour-management relations and to expand the application field of mathematics in the field of management. The provided management method gives opportunity to get rid of centuries old bureaucracy because it enables one to substitute the considerable part of administrative - bureaucratic apparatus as well as many standard acts with one functional relationship.