949 resultados para Pruning operators


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ABSTRACT: Massive synaptic pruning following over-growth is a general feature of mammalian brain maturation. Pruning starts near time of birth and is completed by time of sexual maturation. Trigger signals able to induce synaptic pruning could be related to dynamic functions that depend on the timing of action potentials. Spike-timing-dependent synaptic plasticity (STDP) is a change in the synaptic strength based on the ordering of pre- and postsynaptic spikes. The relation between synaptic efficacy and synaptic pruning suggests that the weak synapses may be modified and removed through competitive "learning" rules. This plasticity rule might produce the strengthening of the connections among neurons that belong to cell assemblies characterized by recurrent patterns of firing. Conversely, the connections that are not recurrently activated might decrease in efficiency and eventually be eliminated. The main goal of our study is to determine whether or not, and under which conditions, such cell assemblies may emerge out of a locally connected random network of integrate-and-fire units distributed on a 2D lattice receiving background noise and content-related input organized in both temporal and spatial dimensions. The originality of our study stands on the relatively large size of the network, 10,000 units, the duration of the experiment, 10E6 time units (one time unit corresponding to the duration of a spike), and the application of an original bio-inspired STDP modification rule compatible with hardware implementation. A first batch of experiments was performed to test that the randomly generated connectivity and the STDP-driven pruning did not show any spurious bias in absence of stimulation. Among other things, a scale factor was approximated to compensate for the network size on the ac¬tivity. Networks were then stimulated with the spatiotemporal patterns. The analysis of the connections remaining at the end of the simulations, as well as the analysis of the time series resulting from the interconnected units activity, suggest that feed-forward circuits emerge from the initially randomly connected networks by pruning. RESUME: L'élagage massif des synapses après une croissance excessive est une phase normale de la ma¬turation du cerveau des mammifères. L'élagage commence peu avant la naissance et est complété avant l'âge de la maturité sexuelle. Les facteurs déclenchants capables d'induire l'élagage des synapses pourraient être liés à des processus dynamiques qui dépendent de la temporalité rela¬tive des potentiels d'actions. La plasticité synaptique à modulation temporelle relative (STDP) correspond à un changement de la force synaptique basé sur l'ordre des décharges pré- et post- synaptiques. La relation entre l'efficacité synaptique et l'élagage des synapses suggère que les synapses les plus faibles pourraient être modifiées et retirées au moyen d'une règle "d'appren¬tissage" faisant intervenir une compétition. Cette règle de plasticité pourrait produire le ren¬forcement des connexions parmi les neurones qui appartiennent à une assemblée de cellules caractérisée par des motifs de décharge récurrents. A l'inverse, les connexions qui ne sont pas activées de façon récurrente pourraient voir leur efficacité diminuée et être finalement éliminées. Le but principal de notre travail est de déterminer s'il serait possible, et dans quelles conditions, que de telles assemblées de cellules émergent d'un réseau d'unités integrate-and¬-fire connectées aléatoirement et distribuées à la surface d'une grille bidimensionnelle recevant à la fois du bruit et des entrées organisées dans les dimensions temporelle et spatiale. L'originalité de notre étude tient dans la taille relativement grande du réseau, 10'000 unités, dans la durée des simulations, 1 million d'unités de temps (une unité de temps correspondant à une milliseconde), et dans l'utilisation d'une règle STDP originale compatible avec une implémentation matérielle. Une première série d'expériences a été effectuée pour tester que la connectivité produite aléatoirement et que l'élagage dirigé par STDP ne produisaient pas de biais en absence de stimu¬lation extérieure. Entre autres choses, un facteur d'échelle a pu être approximé pour compenser l'effet de la variation de la taille du réseau sur son activité. Les réseaux ont ensuite été stimulés avec des motifs spatiotemporels. L'analyse des connexions se maintenant à la fin des simulations, ainsi que l'analyse des séries temporelles résultantes de l'activité des neurones, suggèrent que des circuits feed-forward émergent par l'élagage des réseaux initialement connectés au hasard.

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The questions studied in this thesis are centered around the moment operators of a quantum observable, the latter being represented by a normalized positive operator measure. The moment operators of an observable are physically relevant, in the sense that these operators give, as averages, the moments of the outcome statistics for the measurement of the observable. The main questions under consideration in this work arise from the fact that, unlike a projection valued observable of the von Neumann formulation, a general positive operator measure cannot be characterized by its first moment operator. The possibility of characterizing certain observables by also involving higher moment operators is investigated and utilized in three different cases: a characterization of projection valued measures among all the observables is given, a quantization scheme for unbounded classical variables using translation covariant phase space operator measures is presented, and, finally, a mathematically rigorous description is obtained for the measurements of rotated quadratures and phase space observables via the high amplitude limit in the balanced homodyne and eight-port homodyne detectors, respectively. In addition, the structure of the covariant phase space operator measures, which is essential for the above quantization, is analyzed in detail in the context of a (not necessarily unimodular) locally compact group as the phase space.

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Tämä diplomityö on tehty Lappeenrannassa Telecom Business Research Centerin 5T-projektiin liittyen. Työssä tutkitaan matkaviestinnän lisäarvopalveluiden liiketoimintakonsepteja operaattoreiden näkökulmasta. Lisäarvopalvelut laajentavat operaattoreiden palveluvalikoimaa. Niiden osuuden telekommunikaatioalan yritysten ja erityisesti operaattoreiden tuotoista on ennustettu kasvavan huomattavasti. Työn tärkeimpänä tavoitteena on tuoda uusia näkökulmia ja lisätä ymmärrystä lisäarvopalveluiden liiketoimintakonseptin rakentamisprosessista. Tätä tietämystä käytetään edesauttamaan työn empiirisessä osuudessa tutkitun Content Gateway -tuotteen liiketoimintaa. Tarjoamalla nopean liitynnän ja laskutuskanavan ulkopuolisten palveluntarjoajien ja operaattorin välille tämä tuote mahdollistaa operaattorille ja palveluntarjoajille lisäarvopalveluiden liiketoiminnan käynnistämisen. Lisäarvopalveluiden arvonluontiprosessi vaatii lukuisia yhteistyötä tekeviä osapuolia, joiden yhteistoiminta on dynaamista ja tiedonvälitys avointa, interaktiivista ja nopeaa. Arvonluontiin liittyy myös monia konvergoituvia kehityssuuntia. Perinteinen arvoketjuajattelu on riittämätön uuteen, verkottuneeseen toimintaympäristöön ja sen tilalle on tullut modernimpi arvoverkostomalli. Arvoverkosto luo kilpailuetunsa muita verkostoja vastaan jakamalla resurssit ja kompetenssit optimaalisesti ja liittämällä strategisen ja operationaalisen johtamisen kulttuurit toisiinsa. Tässä työssä verrataan arvoverkoston teoreettisia tavoitteita kahteen lisäarvopalveluiden liiketoimintakonseptiin. Näistä ensimmäinen, i-mode –niminen konsepti on valittu vertailuun edistyksellisyytensä ja tulevaa kehitystä ennakoivien ominaispiirteidensä vuoksi. Toinen esimerkkikonsepti on rakennettu edellä mainitun Content Gateway -tuotteen ympärille. Tutkimus sisältää mm. liikekumppaneiden hankinnan, ansaintalogiikoiden ja verkostojen johtamisen analysoinnin. Työn tuloksena on saatu ohjeita siihen, miten operaattori voi rakentaa tällaista konseptia ja mitä seikkoja tulee ottaa huomioon erityisesti sanomapalveluihin liittyvässä liiketoiminnassa.

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This study aimed to evaluate the growth of plants and the precocity of strawberry production under different root pruning intensities at planting time. Bare roots plants with 12 millimeters crown diameter produced in nurseries from the Patagonia region, Argentina were used. The planting was carried out on May 12th 2010 into experimental plots with non-fumigated soil. The treatments consisted of three cultivars (Camarosa, Florida Festival and Camino Real) and three pruning intensities (1/3, 2/3 and no pruning) on the total root length of the plants. The experimental design used was a randomized block design in a 3x3 factorial arrangement with three replications and 12 plants per plot and density of 11.1 plants m-2. Mature fruits were harvested from July 15th to December 14th 2010 and the production of fresh fruit was determined. There was no significative interaction between cultivars and pruning intensity. 'Camarosa' and 'Florida Festival' plants showed precocity and had the most abundant and heavier fruits during the precocity period. The different root pruning intensities did not affect the assessed variables. It was concluded that, in order to facilitate strawberry planting of the cultivars Camarosa, Florida Festival and Camino Real root pruning is possible, with no damages on plant growth and development, precocity and early fruit production.

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Distortion risk measures summarize the risk of a loss distribution by means of a single value. In fuzzy systems, the Ordered Weighted Averaging (OWA) and Weighted Ordered Weighted Averaging (WOWA) operators are used to aggregate a large number of fuzzy rules into a single value. We show that these concepts can be derived from the Choquet integral, and then the mathematical relationship between distortion risk measures and the OWA and WOWA operators for discrete and finite random variables is presented. This connection offers a new interpretation of distortion risk measures and, in particular, Value-at-Risk and Tail Value-at-Risk can be understood from an aggregation operator perspective. The theoretical results are illustrated in an example and the degree of orness concept is discussed.

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Globalization has increased transport aggregates’ demand. Whilst transport volumes increase, ecological values’im portance has sharpened: carbon footprint has become a measure known world widely. European Union together with other communities emphasizes friendliness to the environment: same trend has extended to transports. As a potential substitute for road transport is noted railway transport, which decreases the congestions and lowers the emission levels. Railway freight market was liberalized in the European Union 2007, which enabled new operators to enter the markets. This research had two main objectives. Firstly, it examined the main market entry strategies utilized and the barriers to entry confronted by the operators who entered the markets after the liberalization. Secondly, the aim was to find ways the governmental organization could enhance its service towards potential railway freight operators. Research is a qualitative case study, utilizing descriptive analytical research method with a normative shade. Empirical data was gathered by interviewing Swedish and Polish railway freight operators by using a semi-structured theme-interview. This research provided novel information by using first-hand data; topic has been researched previously by utilizing second-hand data and literature analyses. Based on this research, rolling stock acquisition, needed investments and bureaucracy generate the main barriers to entry. The research results show that the mostly utilized market entry strategies are start-up and vertical integration. The governmental organization could enhance the market entry process by organizing courses, paying extra attention on flexibility, internal know-how and educating the staff.

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The aim of this work is to study the conservation laws of continuous means mechanics and also to extend the Hamiltonian method for these kind of systems in order to valid for non-potential operators through variational approach. Besides illustrating with various examples of mechanical applications we also introduce in this work the new technique in order to treat such problems as the non-potential problem.

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The objective of this work was to evaluate the selectivity of clomazone in two formulations and S-metolachlor applied on shoots of different sizes after pruning of 'Baianinha' cassava. The experiment was arranged in a randomized block design in a factorial 5 x 2 (5 treatments x 2 sizes of shoots after pruning - 10 and 33 cm) with four replications. The herbicides evaluated were: clomazone (encapsulated suspension - 900 g h-1), clomazone (encapsulated suspension - 1,080 g ha-1), clomazone (emulsifiable concentrate 900 g ha-1), S-metolachlor (1,920 g ha-1) and an untreated control. During the experiment, all plots were kept free of weed interference by hand weeding. It was concluded that both the formulations of clomazone and S-metolachlor were selective when applied on both the shoot sizes evaluated. However, the application of S-metolachlor on 33 cm shoots gave higher selectivity to 'Baianinha' cassava plants.

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Logistics infrastructure and transportation services have been the liability of countries and governments for decades, or these have been under strict regulation policies. One of the first branches opened for competition in EU as well as in other continents, has been air transports (operators, like passenger and freight) and road transports. These have resulted on lower costs, better connectivity and in most of the cases higher service quality. However, quite large amount of other logistics related activities are still directly (or indirectly) under governmental influence, e.g. railway infrastructure, road infrastructure, railway operations, airports, and sea ports. Due to the globalization, governmental influence is not that necessary in this sector, since transportation needs have increased with much more significant phase as compared to economic growth. Also freight transportation needs do not correlate with passenger side, due to the reason that only small number of areas in the world have specialized in the production of particular goods. Therefore, in number of cases public-private partnership, or even privately owned companies operating in these sub-branches have been identified as beneficial for countries, customers and further economic growth. The objective of this research work is to shed more light on these kinds of experiments, especially in the relatively unknown sub-branches of logistics like railways, airports and sea container transports. In this research work we have selected companies having public listed status in some stock exchange, and have needed amount of financial scale to be considered as serious company rather than start-up phase venture. Our research results show that railways and airports usually need high fixed investments, but have showed in the last five years generally good financial performance, both in terms of profitability and cash flow. In contrary to common belief of prosperity in globally growing container transports, sea vessel operators of containers have not shown that impressive financial performance. Generally margins in this business are thin, and profitability has been sacrificed in front of high growth – this also concerns cash flow performance, which has been lower too. However, as we examine these three logistics sub-branches through shareholder value development angle during time period of 2002-2007, we were surprised to find out that all of these three have outperformed general stock market indexes in this period. More surprising is the result that financially a bit less performing sea container transportation sector shows highest shareholder value gain in the examination period. Thus, it should be remembered that provided analysis shows only limited picture, since e.g. dividends were not taken into consideration in this research work. Therefore, e.g. US railway operators have disadvantage to other in the analysis, since they have been able to provide dividends for shareholders in long period of time. Based on this research work we argue that investment on transportation/logistics sector seems to be safe alternative, which yields with relatively low risk high gain. Although global economy would face smaller growth period, this sector seems to provide opportunities in more demanding situation as well.

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This master thesis work introduces the fuzzy tolerance/equivalence relation and its application in cluster analysis. The work presents about the construction of fuzzy equivalence relations using increasing generators. Here, we investigate and research on the role of increasing generators for the creation of intersection, union and complement operators. The objective is to develop different varieties of fuzzy tolerance/equivalence relations using different varieties of increasing generators. At last, we perform a comparative study with these developed varieties of fuzzy tolerance/equivalence relations in their application to a clustering method.

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The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.