This thesis presents the research work regarding the solution of a localization problem in indoor WLANs by introducing a distributive time division multiplexed localization technique based on the convex semidefinite programming. Convex optimizations have proven to give promising results but have limitations of computational complexity for a larger problem size. In the case of localization problem the size is determined depending on the number of nodes to be localized. Thus a convex localization technique could not be applied to real time tracking of mobile nodes within the WLANs that are already providing computationally intensive real time multimedia services. Here we have developed a distributive technique to circumvent this problem such that we divide a larger network into computationally manageable smaller subnets. The division of a larger network is based on the mobility levels of the nodes. There are two types of nodes in a network; mobile, and stationery. We have placed the mobile nodes into separate subnets which are tagged as mobile whereas the stationary nodes are placed into subnets tagged as stationary. The purpose of this classification of networks into subnets is to achieve a priority-based localization with a higher priority given to mobile subnets. Then the classified subnets are localized by scheduling them in a time division multiplexed way. For this purpose a time-frame is defined consisting of finite number of fixed duration time-slots such that within the slot duration a subnet could be localized. The subnets are scheduled within the frames with a 1:n ratio pattern that is within n number of frames each mobile subnet is localized n times while each stationary subnet consisting of stationary nodes is localized once. By using this priority-based scheduling we have achieved a real time tracking of mobile node positions by using the computationally intensive convex optimization technique. In addition, we present that the resultant distributive technique can be applied to a network having diverse node density that is a network with its nodes varying from very few to large numbers can be localized by increasing frame duration. This results in a scalable technique. In addition to computational complexity, another problem that arises while formulating the distance based localization as a convex optimization problem is the high-rank solution. We have also developed the solution based on virtual nodes to circumvent this problem. Virtual nodes are not real nodes but these are nodes that are only added within the network to achieve low rank realization. Finally, we developed a distributive 3D real-time localization technique that exploited the mobile user behaviour within the multi-storey indoor environments. The estimates of heights by using this technique were found to be coarse. Therefore, it can only be used to identify floors in which a node is located.

Clustering techniques are important for gene expression data analysis. However, efficient computational algorithms for clustering time-series data are still lacking. This work documents two improvements on an existing profile-based greedy algorithm for short time-series data; the first one is implementation of a scaling method on the pre-processing of the raw data to handle some extreme cases; the second improvement is modifying the strategy to generate better clusters. Simulation data and real microarray data were used to evaluate these improvements; this approach could efficiently generate more accurate clusters. A new feature-based algorithm was also developed in which steady state value; overshoot, rise time, settling time and peak time are generated by the 2nd order control system for the clustering purpose. This feature-based approach is much faster and more accurate than the existing profile-based algorithm for long time-series data.

This study analyzes snow maintenance data of Borlänge municipality of Sweden based on the data of 2017 to 2018. The goal of this study is to reduce operational overhead of snow maintenance, for example, fuel and time consumption of the snow maintenance vehicles, work hour of dedicated personnel, etc. Borlänge Energy equipped the snow maintenance vehicles with GPS devices which stored the record of the snow maintenance activities. The initial part of this study obtained insights out of the GPS data by using spatiotemporal data analysis. Derivation of the different snow maintenance treatments (plowing, sanding and salting) as well as the efficiency of the sub-contractors (companies which are responsible for snow maintenance) and inspectors (personnel who are liable to call the subcontractors if they think it is time for snow maintenance) are performed in the beginning of this study. The efficiency of the subcontractors and inspectors are measured to compare their performance with each other. The latter part of this study discusses a simulated annealing-based heuristics technique to find out optimal location for dispatching snow maintenance vehicles. In the existing system of snow maintenance, drivers of the maintenance vehicles decide to start location of maintenance work based on their experience and intuition, which might vary from one driver to another driver. The vehicle dispatch locations are calculated based on the availability of the vehicles. For example, if a subcontractor has three vehicles to perform snow maintenance on a specific road map, the proposed solution would suggest three locations to dispatch those vehicles. The purpose of finding the optimal dispatch location is to reduce the total travel distance of the maintenance vehicles, which yield less fuel and time consumption. The study result shows the average travel distance for 1, 3, and 5 vehicles on 15 road networks. The proposed solution would yield 18% less travel than the existing system of snow maintenance.

BACKGROUND: Social cognitive ability is a significant determinant of functional outcome and deficits in social cognition are a disabling symptom of psychotic disorders. The neurobiological underpinnings of social cognition are not well understood, hampering our ability to ameliorate these deficits. Using ‘resting-state’ fMRI (functional magnetic resonance imaging) and a trans-diagnostic, data-driven analytic strategy, we sought to identify the brain network basis of emotional intelligence, a key domain of social cognition. METHODS: Subjects included 60 participants with a diagnosis of schizophrenia or schizoaffective disorder and 46 healthy comparison participants from three different sites: Beth Israel Deaconess Medical Center, Boston, MA, McLean Hospital, Belmont, MA, and University of Pittsburgh, Pittsburgh, PA. All participants underwent a structural T1/MPRAGE and resting-state fMRI scan. Emotional Intelligence was measured using the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). A connectome-wide analysis of brain connectivity examined how each individual brain voxel’s connectivity correlated with emotional intelligence using multivariate distance matrix regression (MDMR). RESULTS: We identified a region in the left superior parietal lobule (SPL) where individual network topology predicted emotional intelligence. Specifically, the association of this region with the Default Mode Network (DMN) predicted higher emotional intelligence (r = 0.424, p < 0.001) and association with the Dorsal Attention Network (DAN) predicted lower emotional intelligence (r = -0.504, p < 0.001). This correlation was observed in both schizophrenia and healthy comparison participants. These results held true despite corrections for sex, age, race, medication dosage (chlorpromazine equivalents), and full scale IQ (FSIQ), and was replicable per site. Post-hoc analyses showed that membership of the left SPL was entirely within the DMN in high scorers and within the DAN in low scorers. This relationship was also shown to be specific to the identified left SPL region when compared to adjacent regions. Sulcal depth analysis of the left SPL revealed a correlation to emotional intelligence (r = 0.269, p = 0.0075). CONCLUSIONS: Previous studies have demonstrated individual variance in brain network topology but the cognitive or behavioral relevance of these differences was undetermined. We observe that the left SPL, a region of high individual variance at the cytoarchitectonic level, also demonstrates individual variance in its association with large scale brain networks and that network topology predicts emotional intelligence. This is the first demonstration of a clinical phenotype in individual brain network topology. / 2019-07-03T00:00:00Z

The maximum subarray problem is to find the array portion that maximizes the sum of array elements in it. This problem was first introduced by Grenander and brought to computer science by Bentley in 1984. This problem has been branched out into other problems based on their characteristics. k-overlapping maximum subarray problem where the overlapping solutions are allowed, and k-disjoint maximum subarray problem where all the solutions are disjoint from each other are those. For k-overlapping maximum subarray problems, significant improvement have been made since the problem was first introduced. For k-disjoint maximum subarrsy, Ruzzo and Tompa gave an O(n) time solution for one-dimension. This solution is, however, difficult to extend to two-dimensions. While a trivial solution of O(kn^3) time is easily obtainable for two-dimensions, little study has been undertaken to better this. This paper introduces a faster algorithm for the k-disjoint maximum sub-array problem under the conventional RAM model, based on distance matrix multiplication. Also, DMM reuse technique is introduced for the maximum subarray problem based on recursion for space optimization.

Denna rapport avhandlar ett arbete inom ämnet datavetenskap och handlarom utvecklingen av ett system för att studera restidkvoten för sträckor somtrafikeras av Västtrafik, som är en av Sveriges största regionalakollektivtrafikmyndigheter. Restidskvoten anges som förhållandet mellanrestiden med kollektivtrafik och att resa med personbil ([restidkollektivtrafik] / [restid biltrafik]). Med detta som grund har ett system föratt inhämta data om restider med hjälp av Google Maps Directions API samtberäkna restidskvoter och annan metadata utifrån denna insamlade dataskapats. Systemet används till att göra dagliga körningar och lagrar inhämtaddata i en databas hos Västtrafik. Till systemet finns också en dashboard somkan användas för att göra sökningar i databasen som byggts upp och på såsätt hämta, visualisera och analysera önskad data. Restidsdata förkollektivtrafik som erhållits från Google har i stickprov jämförts medrestidsdata från Västtrafik och även om det fanns några avvikelser så stämdede väl överens. Därav dras slutsatsen att data från Google går att använda tillatt beräkna och analysera restidskvoter.

O conhecimento da variabilidade e da relaÃÃo genÃtica entre diferentes acessos de aceroleira à importante para maximizar o uso dos recursos genÃticos nos programas de melhoramento. Neste trabalho tÃm-se como objetivos avaliar a diversidade genÃtica de 56 genÃtipos de aceroleira pertencentes ao Jardim de Sementes e ao Jardim Clonal da Embrapa AgroindÃstria Tropical por meio de marcadores moleculares ISSR, e avaliar a reaÃÃo de genÃtipos de aceroleira à Lasiodiplodia theobromae. Para a avaliaÃÃo da relaÃÃo genÃtica entre os genÃtipos de aceroleira foi calculada a distÃncia genÃtica entre estes tomando-se como base os dados obtidos por meio dos marcadores moleculares ISSR. Uma matriz de distÃncia foi obtida com base no complemento aritmÃtico do Ãndice de Jaccard, a qual foi usada para a formaÃÃo de um dendrograma onde os diferentes genÃtipos foram agrupados. Esse agrupamento foi realizado utilizando-se o mÃtodo hierÃrquico, UPGMA e o mÃtodo de otimizaÃÃo de Tocher. Na identificaÃÃo de genÃtipos resistentes/suscetÃveis à Lasiodiplodia theobromae, foi utilizado o mÃtodo de inoculaÃÃo (Furadeira). A avaliaÃÃo foi realizada em casa de vegetaÃÃo, contemplando a avaliaÃÃo de seis genÃtipos diferentes. Aos 15 dias apÃs a inoculaÃÃo (DAI) foi procedida a avaliaÃÃo externa dos sintomas e a mediÃÃo do comprimento da lesÃo. Na avaliaÃÃo da divergÃncia genÃtica atravÃs de marcadores moleculares observou-se que os genÃtipos 36 (12/7/15), 47 (Barbados) e 46 (Okinawa) foram os mais divergentes entre os 56 genÃtipos avaliados. Os cruzamentos entre os genÃtipos 36 (12/7/15) e 32 (68/1/15), 36 (12/7/15) e 31 (68/1/14), 47 (Barbados) e 2 (8/4/8), 47 (Barbados) e 23 (79/10/9), 46 (Okinawa) e 32 (68/1/15) e entre 46 (Okinawa) e 36 (12/7/15) podem resultar em combinaÃÃes gÃnicas favorÃveis permitindo a seleÃÃo de genÃtipos transgressivos. Buscando identificar clones resistentes os clones 13 (47/5/2), 32 (68/1/15) e 36 (12/7/15) mostraram mais resistentes ao fungo em avaliaÃÃo. Portanto, foi possÃvel identificar variabilidade genÃtica entre os 56 genÃtipos de aceroleira, assim como genÃtipos resistentes à Lasiodiplodia theobromae. Essas informaÃÃes poderÃo ser utilizadas em futuros trabalhos de melhoramento genÃtico da cultura da aceroleira. / The knowledge about genetic variability and relationship among Indian cherry accessions is an important issue to maximize the use of genetic resources in a breeding program. The objectives of this study were to estimate the genetic diversity of 56 Indian cherry genotypes from the seed garden and clone collection of Embrapa AgroindÃstria Tropical using ISSR as molecular markers and to evaluate their reaction to infection by Lasiodiplodia theobromae. In order to evaluate genetic relationship among Indian cherry genotypes the genetic distance was calculated based on ISSR data. A distance matrix was obtained based on the Jaccard index of arithmetic complement which was used to construct a phylogram tree with all 56 acessions. The tree was constructed using the hierarchical method, the unweight pair-grouped (UPGMA) generated tree and the optimizing Tocher method. To identify resistant/susceptible genotypes to L. theobromae, it was developed a drill method of inoculation the fungus into the woody tissue of the plant stem. The work was carried out under greenhouse conditions with six genotypes. Disease occurrence was observed 15 days after inoculation by observing lesion presence and measuring lesion length. Data on the genetic diversity showed that three genotypes, numbered 36, 46 (Okinawa) and 47 (Barbados) were the most divergent among all 56 studied. Crossings between 36 (12/7/15) x 32 (68/1/15), 36 (12/7/15) x 31 (68/1/14), 47 (Barbados) x 2 (8/4/8), 47 (Barbados) x 23 (79/10/9), 46 (Okinawa) x 32 (68/1/15) and 46 (Okinawa) x 36 (12/7/15) may yield favorable genetic combinations allowing a transgressive genotype selection. In the search to identify potentially resistant genotypes, the accessions 13 (47/5/2), 32 (68/1/15) and 36 (12/7/15) attained high level resistance. As a conclusion, it was possible to estimate genetic variability and resistant genotypes to L. theobromae in the Indian cherry population. These results may provide valuable information for the breeding program in the near future.

Changes in chromosome number and structure may cause serious diseases. Cytogenetic tests leadin to set of karyotype are done for detecting these abnormalities. Chromosomes are visualised with proper methods and karyotype is made up most often. Manual karyotyping is time-consuming and expensive task. Because of this, researchers have been developing automated karyotyping systems. Karyotyping systems classify chromosomes into classes based on their characteristic features. Overlapping and bent chromosomes are limitations for automatic classification since they ocur at almost every mitosis. Accuracy and reliability of karyotyping systems still depend on the human intervention. Overcoming of these problems and development of fully automated system is the aim of modern approaches.

The thesis is focused on the recognition methods study used in one-dimensional signal processing. A lot of recognition methods exist, this thesis briefly describes the principle of some of them, e.g. artificial neural networks, fuzzy systems, expert systems and decision trees. Dynamic time warping (DTW) method has been chosen for signal processing available from UBMI database. DTW can be used as a non-linear signal processing method. The result of this method is to determine the similarity of two compared signals on the basis of their distance calculation. One of the reasons for choosing this method was the possibility of various length signal processing. The principle of the method as well as the calculation of the distance between two input data sequences is described in the thesis. DTW path finding method is also mentioned. The method was applied on randomly selected numbers and a set of simulated signals. The method was applied to ECG and action potential signals recorded on the isolated rabbit heart. DTW was used to evaluate shape changes of these signals in repeated phases of the experiment known as ischemia and reperfusion. Selected cardiac cycles were detected and included into different experiment phases on the basis of calculated distance results using DTW. Sensitivity was selected as an evaluative criterion of this classification method. It reached a value of 65%. DTW algorithm was further tested on the selected cardiac cycle mapping to the corresponding minute record in the selected experiment phase. It reached a sensitivity of 68.3%. The motion artifact appearance was monitored using DTW on AP signals. The method functioned more precisely on signals measured in ischemia phases. Along with the above mentioned, the thesis discusses all aspects of heart electrical manifestation activities called as ECG signals and action potentials, such as origin, propagation, recording, post-processing and measuring out.

This work is dedicated to dynamic time warping in biosignal processing, especially it´s application for ECG signals. On the beginning the theoretical notes about cardiography are summarized. Then, the DTW analysis follows along with conditions and demands assessments for it’s successful application. Next, several variants and application possibilities are described. The practical part covers the design of this method, the outputs comprehension, settings optimization and realization of methods related with DTW