Load profile based determination of distribution feeder configuration by dynamic programming

This paper presents a new method to determine feeder reconfiguration scheme considering variable load profile. The objective function consists of system losses, reliability costs and also switching costs. In order to achieve an optimal solution the proposed method compares these costs dynamically and determines when and how it is reasonable to have a switching operation. The proposed method divides a year into several equal time periods, then using particle swarm optimization (PSO), optimal candidate configurations for each period are obtained. System losses and customer interruption cost of each configuration during each period is also calculated. Then, considering switching cost from a configuration to another one, dynamic programming algorithm (DPA) is used to determine the annual reconfiguration scheme. Several test systems were used to validate the proposed method. The obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically.

Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.

A survey: Particle Swarm Optimization based algorithms to solve premature convergence problem

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although, PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, the authors have included a classification of the approaches and they have identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.

Crop Classification using Biologically-inspired Techniques with High Resolution Satellite Image

Remote sensing provides a lucid and effective means for crop coverage identification. Crop coverage identification is a very important technique, as it provides vital information on the type and extent of crop cultivated in a particular area. This information has immense potential in the planning for further cultivation activities and for optimal usage of the available fertile land. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Further, image classification forms the core of the solution to the crop coverage identification problem. No single classifier can prove to satisfactorily classify all the basic crop cover mapping problems of a cultivated region. We present in this paper the experimental results of multiple classification techniques for the problem of crop cover mapping of a cultivated region. A detailed comparison of the algorithms inspired by social behaviour of insects and conventional statistical method for crop classification is presented in this paper. These include the Maximum Likelihood Classifier (MLC), Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) techniques. The high resolution satellite image has been used for the experiments.

Betydelser i barnfamiljsbroschyrer : Systemisk-funktionell analys av den tänkta läsaren och institutionen

This thesis concerns Swedish and Finland-Swedish brochures to families with children, presenting family allowances from the social insurance institutions in the two countries. The aim of the study is to analyse what meanings are conveyed with reference to the conceivable reader and the institution in the brochures. The material consists of information brochures in Swedish from Kela, the social insurance institution of Finland, and Försäkringskassan, the Swedish social insurance agency, issued during 2003–2006. The general theoretical framework is systemic-functional linguistics (SFL) as presented by Halliday & Matthiessen (2004) and Holmberg & Karlsson (2006). The study consists of a quantitative study of the lexical choices of the social insurance brochures. Furthermore, a qualitative process and participant analysis is annotated with the UAM Corpus tool and the results are quantified. Speech functions and modal auxiliaries are analysed qualitatively. The analysis shows that material and relational processes are most common. The relational and verbal processes are used more in the Sweden-Swedish brochures, while the material processes are more common in the Finland-Swedish brochures. The participants in the brochures are the institution, mentioned by its name, and the conceivable reader, directly addressed with “you” (du). In addition, the referent “child” is often mentioned. The participants assigned for the reader are Actor, Receiver, Carrier and Speaker. In the Finland-Swedish texts, the reader is often an Actor, while the reader in the Sweden-Swedish texts is a Carrier. Thus, the conceivable reader is an active participant who takes care of his or her own matters using the internet, communicates actively to the institution and has legal rights and obligations. The institution is visible in the texts but does not have an active role as the name of the institution is mostly used in circumstances. The institution is not often a participant, but when it is, it is Actor, Receiver, Listener and Carrier, expecting the clients to address it. Speech functions are performed in different ways. For instance, questions structure the reading process and commands are realised by modal auxiliaries, not by imperatives. The most common modal auxiliary is kan (can, may), and another common auxiliary is ska (shall, must). Statements are surrounded by subordinate clauses and adverbs that describe situations and criteria. The results of the study suggest that the brochures in the two countries are similar, in particular when produced in similar ways, that is, when the Finland-Swedish texts are not translated. Existing differences reflect the differences in the institutions, the social insurance systems and the cultural contexts. KEYWORDS: Finland-Swedish, Swedish, comparative analysis, SFL, discourse analysis, administrative language, institutional discourse, institutional communication

Quantum behaved Particle Swarm Optimization (QPSO) for multi-objective design optimization of composite structures

We present a new, generic method/model for multi-objective design optimization of laminated composite components using a novel multi-objective optimization algorithm developed on the basis of the Quantum behaved Particle Swarm Optimization (QPSO) paradigm. QPSO is a co-variant of the popular Particle Swarm Optimization (PSO) and has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; Failure Mechanism based Failure criteria, Maximum stress failure criteria and the Tsai-Wu Failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences as well as fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. Also, the performance of QPSO is compared with the conventional PSO.

Swarm intelligence-based solver for parameter estimation of laboratory through-diffusion transport of contaminants

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated be fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. Thes parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.

Population dynamics of blue mussels in a variable environment at the edge of their range

Spatial and temporal variation in the abundance of species can often be ascribed to spatial and temporal variation in the surrounding environment. Knowledge of how biotic and abiotic factors operate over different spatial and temporal scales in determining distribution, abundance, and structure of populations lies at the heart of ecology. The major part of the current ecological theory stems from studies carried out in central parts of the distributional range of species, whereas knowledge of how marginal populations function is inadequate. Understanding how marginal populations, living at the edge of their range, function is however in a key position to advance ecology and evolutionary biology as scientific disciplines. My thesis focuses on the factors affecting dynamics of marginal populations of blue mussels (Mytilus edulis) living close to their tolerance limits with regard to salinity. The thesis aims to highlight the dynamics at the edge of the range and contrast these with dynamics in more central parts of the range in order to understand the potential interplay between the central and the marginal part in the focal system. The objectives of the thesis are approached by studies on: (1) factors affecting regional patterns of the species, (2) long-term temporal dynamics of the focal species spaced along a regional salinity gradient, (3) selective predation by increasing populations of roach (Rutilus rutilus) when feeding on their main food item, the blue mussel, (4) the primary and secondary effects of local wave exposure gradients and (5) the role of small-scale habitat heterogeneity as determinants of large-scale pattern. The thesis shows that populations of blue mussels are largely determined by large scale changes in sea water salinity, affecting mainly recruitment success and longevity of local populations. In opposite to the traditional view, the thesis strongly indicate that vertebrate predators strongly affect abundance and size structure of blue mussel populations, and that the role of these predators increases towards the margin where populations are increasingly top-down controlled. The thesis also indicates that the positive role of biogenic habitat modifiers increases towards the marginal areas, where populations of blue mussels are largely recruitment limited. Finally, the thesis shows that local blue mussel populations are strongly dependent on high water turbulence, and therefore, dense populations are constrained to offshore habitats. Finally, the thesis suggests that ongoing sedimentation of rocky shores is detrimental for the species, affecting recruitment success and post-recruit survival, pushing stable mussel beds towards offshore areas. Ongoing large scale changes in the Baltic Sea, especially dilution processes with attendant effects, are predicted to substantially contract the distributional range of the mussel, but also affect more central populations. The thesis shows that in order to understand the functioning of marginal populations, research should (1) strive for multi-scale approaches in order to link ecosystem patterns with ecosystem processes, and (2) challenge the prevailing tenets that origin from research carried out in central areas that may not be valid at the edge.

Short- and long-term consequences of food resources on Ural owl Strix uralensis reproduction

Life-history theory states that although natural selection would favour a maximisation of both reproductive output and life-span, such a combination can not be achieved in any living organism. According to life-history theory the reason for the fact that not all traits can be maximised simultaneously is that different traits compete with each other for resources. These relationships between traits that constrain the simultaneous evolution of two or more traits are called trade-offs. Therefore, during different life-stages an individual needs to optimise its allocation of resources to life-history components such as growth, reproduction and survival. Resource limitation acts on these traits and therefore investment in one trait, e.g. reproduction, reduces the resources available for investment in another trait, e.g. residual reproduction or survival. In this thesis I study how food resources during different stages of the breeding event affect reproductive decisions in the Ural owl (Strix uralensis) and the consequences of these decisions on parents and offspring. The Ural owl is a suitable study species for such studies in natural populations since they are long-lived, site-tenacious, and feed on voles. The vole populations in Fennoscandia fluctuate in three- to four-year cycles, which create a variable food environment for the Ural owls to cope with. The thesis gives new insight in reproductive costs and their consequences in natural animal populations with emphasis on underlying physiological mechanisms. I found that supplementary fed Ural owl parents invest supplemented food resources during breeding in own self-maintenance instead of allocating those resources to offspring growth. This investment in own maintenance instead of improving current reproduction had carry-over effects to the following year in terms of increased reproductive output. Therefore, I found evidence that reduced reproductive costs improves future reproductive performance. Furthermore, I found evidence for the underlying mechanism behind this carry-over effect of supplementary food on fecundity. The supplementary-fed parents reduced their feeding investment in the offspring compared to controls, which enabled the fed female parents to invest the surplus resources in parasite resistance. Fed female parents had lower blood parasite loads than control females and this effect lasted until the following year when also reproductive output was increased. Hence, increased investment in parasite resistance when resources are plentiful has the potential to mediate positive carry-over effects on future reproduction. I further found that this carry-over effect was only present when potentials for future reproduction were good. The thesis also provides new knowledge on resource limitation on maternal effects. I found that increased resources prior to egg laying improve the condition and health of Ural owl females and enable them to allocate more resources to reproduction than control females. These additional resources are not allocated to increase the number of offspring, but instead to improve the quality of each offspring. Fed Ural owl females increased the size of their eggs and allocated more health improving immunological components into the eggs. Furthermore, the increased egg size had long-lasting effects on offspring growth, as offspring from larger eggs were heavier at fledging. Limiting resources can have different short- and long-term consequences on reproductive decisions that affect both offspring number and quality. In long-lived organisms, such as the Ural owl, it appears to be beneficial in terms of fitness to invest in long breeding life-span instead of additional investment in current reproduction. In Ural owls, females can influence the phenotypic quality of the offspring by transferring additional resources to the eggs that can have long-lasting effects on growth.

Kin selection, social polymorphism, and reproductive allocation in ants

Social groups are common across animal species. The reasons for grouping are straightforward when all individuals gain directly from cooperating. However, the situation becomes more complex when helping entails costs to the personal reproduction of individuals. Kin selection theory has offered a fruitful framework to explain such cooperation by stating that individuals may spread their genes not only through their own reproduction, but also by helping related individuals reproduce. However, kin selection theory also implicitly predicts conflicts when groups consist of non-clonal individuals, i.e. relatedness is less than one. Then, individual interests are not perfectly aligned, and each individual is predicted to favour the propagation of their own genome over others. Social insects provide a solid study system to study the interplay between cooperation and conflict. Breeding systems in social insects range from solitary breeding to eusocial colonies displaying complete division of reproduction between the fertile queen and the sterile worker caste. Within colonies, additional variation is provided by the presence of several reproductive individuals. In many species, the queen mates multiply, which causes the colony to consist of half-sib instead of full-sib offspring. Furthermore, in many species colonies contain multiple breeding queens, which further dilutes relatedness between colony members. Evolutionary biology is thus faced with the challenge to answer why such variation in social structure exists, and what the consequences are on the individual and population level. The main part of this thesis takes on this challenge by investing the dynamics of socially polymorphic ant colonies. The first four chapters investigate the causes and consequences of different social structures, using a combination of field studies, genetic analyses and laboratory experiments. The thesis ends with a theoretical chapter focusing on different social interactions (altruism and spite), and the evolution of harming traits. The main results of the thesis show that social polymorphism has the potential to affect the behaviour and traits of both individuals and colonies. For example, we found that genetic polymorphism may increase the phenotypic variation between individuals in colonies, and that socially polymorphic colonies may show different life history patterns. We also show that colony cohesion may be enhanced even in multiple-queen colonies through patterns of unequal reproduction between queens. However, the thesis also demonstrates that spatial and temporal variation between both populations and environments may affect individual and colony traits, to the degree that results obtained in one place or at one time may not be applicable in other situations. This opens up potential further areas of research to explain these differences.

Accurate Parameter Estimation of Contaminant Transport Inverse Problem using Particle Swarm Optimization

Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.

Agents Based Algorithms for Design Parameter Estimation in Contaminant Transport Inverse Problems

A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigen values obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigen values from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigen values are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.

Primary Dislocation of the Patella : A Clinical Study

A total of 177 patients with primary dislocation of the patella (PDP) were admitted to two trauma centers in Helsinki, Finland during 1991 to 1992. The inclusion criteria were: 1. Acute (≤14 days old) first-time lateral dislocation of the patella. 2. No previous knee operations or major knee injuries. 3. No ligament injuries to be repaired. 4. No osteochondral fractures requiring fixation. 50 patients were excluded. 30 of these excluded patients would have met the inclusion criteria, 19 patients received treatment by consultants not involved in the study, 7 refused to participate and 4 had an erroneous randomization. 127 patients including, 82 females, were then randomized to have either tailor-made operative procedure (group O) or conservative treatment (group C). The aftercare was similar for both groups. The mean age of the patients was 20 (9-47) years. All patients were subjected to analysis of trauma history (starting position and knee movement during the dislocation), examination under anesthesia (EUA) and arthroscopy. 70 patients (52 females) were randomized by their odd year of birth to operative group O and 57 patients (30 females) by their even year of birth to conservative group C. The diagnosis of PDP was based on locked dislocation in 68 patients, on dislocatability in EUA in 47 patients, and on subluxation in EUA combined with typical intra-articular lesions in 12 patients. In group O, 63 patients had exploration of the injuries on the medial side of the knee and tailor made reconstruction added with lateral release in 54 cases. The medial injury was operated by suturing in 39 patients, by duplication in 18 patients and by additional augmentation of the medial patellofemoral ligament (MPFL) with adductor magnus tenodesis in 6 patients. 7 patients, without locking in trauma history and only subluxation in EUA had only lateral release for realignment. In adductor magnus tenodesis the proximal end of the distal tendinous part was rerouted to the upper medial border of the patella. In the conservative group C, the treatment was adjusted to the extent of patellar displacement in EUA. Patients with dislocation in EUA had 3 weeks’ immobilization with the knee in slight flexion. Mobilization was started with a soft patellar stabilizing orthosis (PSO) used for additional three weeks. The patients with subluxation in EUA wore an orthosis for six weeks. The aftercare was similar in group O. The outcome was similar in both groups. After an average of 25 (20-45) months´ follow-up, the subjective result was better in group C in respect of the mean Hughston VAS knee score (87 for group O and 90 for group C, p=0.04, visual analog scale), but similar in terms of the patient’s own overall opinion and the mean Lysholm II knee score. Recurrent instability episodes occurred in 18 patients in group O and in 20 patients in group C. After an average of 7 (6-9) years´ follow-up, the groups did not show statistical difference either in respect of the patient’s own overall opinion, or the mean Hughston VAS and Kujala knee scores. The proportions of stable patellae was 25/70 (36%) in group O and 17/57 (30%) in group O (p=0.5). In a multivariate risk analysis, there was a correlation between low Kujala score (<90) as dependent parameter and female gender (OR: 3.5; 95% CI: 1.4-9.0), and loose body on primary radiographs (OR: 4.1; 95% CI: 1.2-15). Recurrent instability correlated with young age at the time of PDP (OR: 0.9; 95% CI: 0.8-1.0/year). Girls with open tibial apophysis had the worst prognosis for instability (88%; 95% CI: 77-98). The most common mechanisms in trauma history of the patients were movement to flexion from a straight start (78%) and movement to extension from a well-bent start (8%). Spontaneous relocation of the patella had taken place in 13/39 of girls, in 11/21 of boys, in 26/42 of women and in 17/24 of men with skeletal maturity of the tibia. The dislocation in EUA was non-rotating in 96/126 patients followed by outward rotating dislocation in 14/126 patients. Operative treatment policy in PDP is not recommended. Locking tendency of the patella in PDP depended on the skeletal maturation. Recurrence rate after PDP was higher than expected.

Urban satellite image classification using biologically inspired techniques

This paper focuses on optimisation algorithms inspired by swarm intelligence for satellite image classification from high resolution satellite multi- spectral images. Amongst the multiple benefits and uses of remote sensing, one of the most important has been its use in solving the problem of land cover mapping. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Image classification forms the core of the solution to the land cover mapping problem. No single classifier can prove to satisfactorily classify all the basic land cover classes of an urban region. In both supervised and unsupervised classification methods, the evolutionary algorithms are not exploited to their full potential. This work tackles the land map covering by Ant Colony Optimisation (ACO) and Particle Swarm Optimisation (PSO) which are arguably the most popular algorithms in this category. We present the results of classification techniques using swarm intelligence for the problem of land cover mapping for an urban region. The high resolution Quick-bird data has been used for the experiments.

Vector evaluated particle swarm optimization (VEPSO) for multi-objective design optimization of composite structures

We present a generic method/model for multi-objective design optimization of laminated composite components, based on vector evaluated particle swarm optimization (VEPSO) algorithm. VEPSO is a novel, co-evolutionary multi-objective variant of the popular particle swarm optimization algorithm (PSO). In the current work a modified version of VEPSO algorithm for discrete variables has been developed and implemented successfully for the, multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; failure mechanism based failure criteria, Maximum stress failure criteria and the Tsai-Wu failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. (C) 2007 Elsevier Ltd. All rights reserved.