A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Adaptive optimization schemes for mobile VoIP applications Battery life and call quality aspects

In this thesis programmatic, application-layer means for better energy-efficiency in the VoIP application domain are studied. The work presented concentrates on optimizations which are suitable for VoIP-implementations utilizing SIP and IEEE 802.11 technologies. Energy-saving optimizations can have an impact on perceived call quality, and thus energy-saving means are studied together with those factors affecting perceived call quality. In this thesis a general view on a topic is given. Based on theory, adaptive optimization schemes for dynamic controlling of application's operation are proposed. A runtime quality model, capable of being integrated into optimization schemes, is developed for VoIP call quality estimation. Based on proposed optimization schemes, some power consumption measurements are done to find out achievable advantages. Measurement results show that a reduction in power consumption is possible to achieve with the help of adaptive optimization schemes.

Genome-wide analysis of adaptive molecular evolution in the carnivorous plant Utricularia gibba

The genome of the bladderwort Utricularia gibba provides an unparalleled opportunity to uncover the adaptive landscape of an aquatic carnivorous plant with unique phenotypic features such as absence of roots, development of water-filled suction bladders, and a highly ramified branching pattern. Despite its tiny size, the U. gibba genome accommodates approximately as many genes as other plant genomes. To examine the relationship between the compactness of its genome and gene turnover, we compared the U. gibba genome with that of four other eudicot species, defining a total of 17,324 gene families (orthogroups). These families were further classified as either 1) lineage-specific expanded/contracted or 2) stable in size. The U. gibba-expanded families are generically related to three main phenotypic features: 1) trap physiology, 2) key plant morphogenetic/developmental pathways, and 3) response to environmental stimuli, including adaptations to life in aquatic environments. Further scans for signatures of protein functional specialization permitted identification of seven candidate genes with amino acid changes putatively fixed by positive Darwinian selection in the U. gibba lineage. The Arabidopsis orthologs of these genes (AXR, UMAMIT41, IGS, TAR2, SOL1, DEG9, and DEG10) are involved in diverse plant biological functions potentially relevant for U. gibba phenotypic diversification, including 1) auxin metabolism and signal transduction, 2) flowering induction and floral meristem transition, 3) root development, and 4) peptidases. Taken together, our results suggest numerous candidate genes and gene families as interesting targets for further experimental confirmation of their functional and adaptive roles in the U. gibba's unique lifestyle and highly specialized body plan.

Shout and Act: an Algorithm for Digital Objects Preservation Inspired from Rescue Robots

We adapt the Shout and Act algorithm to Digital Objects Preservation where agents explore file systems looking for digital objects to be preserved (victims). When they find something they “shout” so that agent mates can hear it. The louder the shout, the urgent or most important the finding is. Louder shouts can also refer to closeness. We perform several experiments to show that this system works very scalably, showing that heterogeneous teams of agents outperform homogeneous ones over a wide range of tasks complexity. The target at-risk documents are MS Office documents (including an RTF file) with Excel content or in Excel format. Thus, an interesting conclusion from the experiments is that fewer heterogeneous (varying skills) agents can equal the performance of many homogeneous (combined super-skilled) agents, implying significant performance increases with lower overall cost growth. Our results impact the design of Digital Objects Preservation teams: a properly designed combination of heterogeneous teams is cheaper and more scalable when confronted with uncertain maps of digital objects that need to be preserved. A cost pyramid is proposed for engineers to use for modeling the most effective agent combinations

An energy efficient vertical handover decision algorithm

As wireless communications evolve towards heterogeneousnetworks, mobile terminals have been enabled tohandover seamlessly from one network to another. At the sametime, the continuous increase in the terminal power consumptionhas resulted in an ever-decreasing battery lifetime. To that end,the network selection is expected to play a key role on howto minimize the energy consumption, and thus to extend theterminal lifetime. Hitherto, terminals select the network thatprovides the highest received power. However, it has been provedthat this solution does not provide the highest energy efficiency.Thus, this paper proposes an energy efficient vertical handoveralgorithm that selects the most energy efficient network thatminimizes the uplink power consumption. The performance of theproposed algorithm is evaluated through extensive simulationsand it is shown to achieve high energy efficiency gains comparedto the conventional approach.

Neural mechanisms underlying adaptive actions after slips

An increase in cognitive control has been systematically observed in responses produced immediately after the commission of an error. Such responses show a delay in reaction time (post-error slowing) and an increase in accuracy. To characterize the neurophysiological mechanism involved in the adaptation of cognitive control, we examined oscillatory electrical brain activity by electroencephalogram and its corresponding neural network by event-related functional magnetic resonance imaging in three experiments. We identified a new oscillatory thetabeta component related to the degree of post-error slowing in the correct responses following an erroneous trial. Additionally, we found that the activity of the right dorsolateral prefrontal cortex, the right inferior frontal cortex, and the right superior frontal cortex was correlated with the degree of caution shown in the trial following the commission of an error. Given the overlap between this brain network and the regions activated by the need to inhibit motor responses in a stop-signal manipulation, we conclude that the increase in cognitive control observed after the commission of an error is implemented through the participation of an inhibitory mechanism.

Stress testing and risk evaluation of new capacity payment algorithm proposed by Market Council

In the Russian Wholesale Market, electricity and capacity are traded separately. Capacity is a special good, the sale of which obliges suppliers to keep their generating equipment ready to produce the quantity of electricity indicated by the System Operator. The purpose of the formation of capacity trading was the maintenance of reliable and uninterrupted delivery of electricity in the wholesale market. The price of capacity reflects constant investments in construction, modernization and maintenance of power plants. So, the capacity sale creates favorable conditions to attract investments in the energy sector because it guarantees the investor that his investments will be returned.

Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Solving Leontief Input-Output Model with Trapezoidal Fuzzy Numbers and Gauss-Seidel Algorithm

In this work a fuzzy linear system is used to solve Leontief input-output model with fuzzy entries. For solving this model, we assume that the consumption matrix from di erent sectors of the economy and demand are known. These assumptions heavily depend on the information obtained from the industries. Hence uncertainties are involved in this information. The aim of this work is to model these uncertainties and to address them by fuzzy entries such as fuzzy numbers and LR-type fuzzy numbers (triangular and trapezoidal). Fuzzy linear system has been developed using fuzzy data and it is solved using Gauss-Seidel algorithm. Numerical examples show the e ciency of this algorithm. The famous example from Prof. Leontief, where he solved the production levels for U.S. economy in 1958, is also further analyzed.

GAMS MINLP Solver comparisons and some improvements to the AlphaECP algorithm

I doktorsavhandlingen undersöks förmågan att lösa hos ett antal lösare för optimeringsproblem och ett antal svårigheter med att göra en rättvis lösarjämförelse avslöjas. Dessutom framläggs några förbättringar som utförts på en av lösarna som heter GAMS/AlphaECP. Optimering innebär, i det här sammanhanget, att finna den bästa möjliga lösningen på ett problem. Den undersökta klassen av problem kan karaktäriseras som svårlöst och förekommer inom ett flertal industriområden. Målet har varit att undersöka om det finns en lösare som är universellt snabbare och hittar lösningar med högre kvalitet än någon av de andra lösarna. Det kommersiella optimeringssystemet GAMS (General Algebraic Modeling System) och omfattande problembibliotek har använts för att jämföra lösare. Förbättringarna som presenterats har utförts på GAMS/AlphaECP lösaren som baserar sig på skärplansmetoden Extended Cutting Plane (ECP). ECP-metoden har utvecklats främst av professor Tapio Westerlund på Anläggnings- och systemteknik vid Åbo Akademi.

Software for calculation of reservoir active capacity with the sequent-peak algorithm

It is presented a software developed with Delphi programming language to compute the reservoir's annual regulated active storage, based on the sequent-peak algorithm. Mathematical models used for that purpose generally require extended hydrological series. Usually, the analysis of those series is performed with spreadsheets or graphical representations. Based on that, it was developed a software for calculation of reservoir active capacity. An example calculation is shown by 30-years (from 1977 to 2009) monthly mean flow historical data, from Corrente River, located at São Francisco River Basin, Brazil. As an additional tool, an interface was developed to manage water resources, helping to manipulate data and to point out information that it would be of interest to the user. Moreover, with that interface irrigation districts where water consumption is higher can be analyzed as a function of specific seasonal water demands situations. From a practical application, it is possible to conclude that the program provides the calculation originally proposed. It was designed to keep information organized and retrievable at any time, and to show simulation on seasonal water demands throughout the year, contributing with the elements of study concerning reservoir projects. This program, with its functionality, is an important tool for decision making in the water resources management.