Use of the Retarded Solution-Reprecipitation Process to Attain a Higher Initial Permeability in MnZn Ferrites

We investigated the effect of various amounts of liquid phase on microstructure development during sintering and the resulting magnetic permeability of MnZn ferrite (MZF) samples. Our results revealed that the microstructure and the final magnetic permeability depend on the thickness of the liquid-phase film during sintering. The solution-reprecipitation (S-R) process, which is associated with an intensive microstructure development in MZF, starts when a continuous liquid-phase film of critical thickness δ_o, which wets the MZF grains, is formed. The solid-state sintering that takes place before the formation of the continuous liquid-phase film is essential for the final microstructure of MZF.     

Optimal Operation of Reservoir Systems using Simulated Annealing

A stochastic search technique, simulated annealing (SA), is used to optimize the operation of multiple reservoirs. Seminal application of annealing technique in general to multi-period, multiple-reservoir systems, along with problem representation and selection of different parameter values used in the annealing algorithm for specific cases is discussed. The search technique is improved with the help of heuristic rules, problem-specific information and concepts from the field of evolutionary algorithms. The technique is tested for application to a benchmark problem of four-reservoir system previously solved using a linear programming formulation and its ability to replicate the global optimum solution is examined. The technique is also applied to a system of four hydropower generating reservoirs in Manitoba, Canada, to derive optimal operating rules. A limited version of this problem is solved using a mixed integer nonlinear programming and results are compared with those obtained using SA. A better objective function value is obtained using simulated annealing than the value from a mixed integer non-linear programming model developed for the same problem. Results obtained from these applications suggest that simulated annealing can be used for obtaining near-optimal solutions for multi-period reservoir operation problems that are computationally intractable.     

Comparison of Representative Heuristic Algorithms for Multi-Objective Reservoir Optimal Operation

Heuristic algorithms (HAs) are widely used in multi-objective reservoir optimal operation (MOROO) due to the rapidity of the calculation and simplicity of their design. The literature usually focuses on one or two categories of HAs and simply reviews the state of the art. To provide an overall understanding and a specific comparison of HAs in MOROO, differential evolution (DE), particle swarm optimisation (PSO), and artificial physics optimisation (APO), which serve as typical examples of the three categories of HAs, are compared in terms of the development and applications using a designed experiment. Besides, the general model with constraints and fitness function, and the solution process using a hybrid feasible domain restoration method and penalty function method are also presented. Taking a designed experiment with multiple scenarios, the mean average of the optimal objective function values, the standard deviation of optimal objective function values, the mean average of the computational time, and population diversity are used for comparisons. Results of the comparisons show that (a) the problem of optimal multipurpose reservoir long-term operation is a mathematic programming problem with narrow feasible region and monotonic objective function; (b) it is easy to obtain the same optimal objective function value, but different optimal solutions using HAs; and (c) comparisons do not result in a clear winner, but DE can be more appropriate for MOROO.

     

On minimum cost isolated failure immune networks

A telecommunications network is isolated failure immune (IFI) if and only if communication between operative sites can be completed as long as network failures are isolated. It is known that the class of minimal IFI networks is equivalent to the class of spanning 2-trees. To the best of our knowledge, this work is the first computational study dealing with the construction of a minimum cost IFI network. The problem is known to be NP-complete. We develop a tabu search based heuristic for solving the minimum cost spanning 2-tree (MCS2T) problem. The complex structure of 2-trees makes the tabu search heuristic highly dependent on the starting solution. We develop four heuristic algorithms to obtain diversified good starting solutions. They are: completion of a 2-tree from a spanning tree, two greedy approaches, and a method based on the recursive definition of a 2-tree. We also formulate an integer programming problem (IP) whose objective function value is a lower bound to the MCS2T problem. We solve the IP by developing a constraint generation scheme. The algorithms were tested on complete random graphs with Euclidean distances and on two real data sets (Civil Aeronautics Board) with instances of 10, 15, 20 and 25 nodes. As a result of this research for small problems (10 and 15 nodes), the heuristic solutions are on average within 0.8% from the optimal solution and for large problems (20 and 25 nodes), the average error is less than 2.8%.     

A quantitative analysis of the unit verification perspective on fault distributions in complex software systems: an operational replication

Unit verification, including software inspections and unit tests, is usually the first code verification phase in the software development process. However, principles of unit verification are weakly explored, mostly due to the lack of data, since unit verification data are rarely systematically collected and only a few studies have been published with such data from industry. Therefore, we explore the theory of fault distributions, originating in the quantitative analysis by Fenton and Ohlsson, in the weakly explored context of unit verification in large-scale software development. We conduct a quantitative case study on a sequence of four development projects on consecutive releases of the same complex software product line system for telecommunication exchanges. We replicate the operationalization from earlier studies, analyzed hypotheses related to the Pareto principle of fault distribution, persistence of faults, effects of module size, and quality in terms of fault densities, however, now from the perspective of unit verification. The patterns in unit verification results resemble those of later verification phases, e.g., regarding the Pareto principle, and may thus be used for prediction and planning purposes. Using unit verification results as predictors may improve the quality and efficiency of software verification.     

Computer Support for Implementation of a Systemic Approach to Water Conflict Resolution

Abstract

Water is an important factor in conflicts among stakeholders at the local, regional, and even international level. Water conflicts have taken many forms, but they almost always arise from the fact that the freshwater resources of the world are not partitioned to match the political borders, nor are they evenly distributed in space and time. Two or more countries share the watersheds of 261 major rivers and nearly half of the land area of the world is in international river basins. Water has been used as a military and political goal. Water has been a weapon of war, and water systems have been targets during the war. A systemic approach has been taken in this research to approach resolution of conflicts over water. By helping stakeholders to explore and resolve the underlying structural causes of conflict our approach offers a significant opportunity for its resolution. We define the five main functional activities for assisting the conflict resolution process as: (i) communication; (ii) problem formulation; (iii) data gathering and information generation; (iv) information sharing; and (v) evaluation of consequences. A computerized technical support is developed in the form of the Conflict Resolution Support System (CRSS) for implementation of a systemic approach to water conflicts. Its principal components include an artificial intelligence-based communication system, a database management system, and a model base management system. At this stage of the development, the model base management system consists of tools for multipurpose reservoir operation, river flow routing, multi-criteria decision-making, spatial data analysis, and other general utilities. A hypothetical river basin with potential conflict between stakeholders with respect to water sharing and flood control is used to demonstrate the utility of the new approach and the computer system developed for its implementation.     

One View of the Future

Abstract

Floods, droughts, water scarcity, and water contamination are some among many water problems that are present today and will be even more noticeable in the future. In the past, many different tools have been used for simulation and optimization of complex water resources systems in order to provide an improved basis for decision making. The continuing evolution of information technology (hardware and software) creates a good environment for the transition to new tools. Application of the systems approach to water resources planning, management, and operations has been established as one of the most important advances made in the field of water resources engineering. Based on the lessons learned, this contribution provides my personal view on the tools to be used in the future. Two paradigm shifts are discussed. The first one is focusing on the complexity of the water resources domain and the complexity of the modelling tools in an environment characterised by continuous rapid technological development. The second one deals with water-related data availability and natural variability of domain variables in time and space affecting the uncertainty of water resources decision making.     

Simple and efficient ion imprinted polymer for recovery of uranium from environmental samples

Ion imprinted polymer material (IIP) was prepared by forming ternary complexes of uranyl imprint ion with 1-(prop-2-en-1-yl)-4-(pyridin-2-ylmethyl)piperazine and methacrylic acid followed by thermal copolymerization with ethylene glycol dimethacrylate as the cross-linking monomer in the presence of 1,1'-azobis(cyclohexanecarbonitrile) initiator and 2-methoxy ethanol porogenic solvent. HCl solution (5 mol/L) was used to leach out the uranyl template ion from the IIP particles. Similarly, the control polymer (CP) material was also prepared exactly under the same conditions as the IIP but without the uranyl ion template. Various parameters such as solution pH, initial concentration, aqueous phase volume, sorbent dosage, contact time and leaching solution volumes were investigated. SEM, IR and BET-surface area and pore size analysis were used for the characterization of IIP and CP materials. The extraction efficiency of the IIP and CP was compared using a batch and SPE mode of extraction. The optimal pH for quantitative removal is 4.0-8.0, sorbent amount is 20 mg, contact time is 20 min and the retention capacity is 120 mg of uranyl ion per g of IIP. The IIP prepared demonstrated superior selectivity towards coexisting cations and therefore it can be used for selective removal of uranium from complex matrices.     

A novel split-and-merge algorithm for hierarchical clustering of Gaussian mixture models

The paper presents a novel split-and-merge algorithm for hierarchical clustering of Gaussian mixture models, which tends to improve on the local optimal solution determined by the initial constellation. It is initialized by local optimal parameters obtained by using a baseline approach similar to k-means, and it tends to approach more closely to the global optimum of the target clustering function, by iteratively splitting and merging the clusters of Gaussian components obtained as the output of the baseline algorithm. The algorithm is further improved by introducing model selection in order to obtain the best possible trade-off between recognition accuracy and computational load in a Gaussian selection task applied within an actual recognition system. The proposed method is tested both on artificial data and in the framework of Gaussian selection performed within a real continuous speech recognition system, and in both cases an improvement over the baseline method has been observed.