This master’s thesis focuses on the issue of measurement of parameters of network traffic of wired and wireless networks. The first part theoretically describes SNMP protocol and application interface API, that form the basis for acquiring and evaluating data. The next section describes known MIKROTIK platform and software solutions for the alternative possibility of implementing a new feature. The last part closely describes the created application. It is a simple information system, whose task is to get information and evaluate it using the known functions. The conclusion of the work is a few tests of this application, assessing the real operation.

This dissertation provides a theoretically grounded framework for investigating "legal rhetoric." By making a distinction between the discursive elements of a Legal system and the broader rhetorical notion of Law, rhetorical critics can better understand the interdependent relationship between citizens, their legal structures, and their cultures. The Legal system represents the forum in which legal disputes are addressed. In contrast, the Law signifies the principles of justice and fairness that give rise to legal disputes addressed by the Legal system. This dissertation emphasizes the important role that media play in disseminating information about specific legal disputes and providing citizens an opportunity to reflect on which principles of justice and fairness are to be valued. This study specifically examines the text, reasoning, and media coverage of Gratz v. Bollinger and Grutter v. Bollinger, two U.S. Supreme Court cases related to the University of Michigan's use of racial classifications in its admissions process. By comparing which arguments and rhetorical elements from the Supreme Court's 2003 decisions were reported in the press, this dissertation both demonstrates the rhetorical concepts of the "Law" and the "Legal System" and suggests how citizens and rhetorical scholars can more fully critique legal texts. / text

Thèse--Théologie protestante--Genève, 1973. N°: n °549. / Bibliogr. p. 273-296.

abstract: The purpose of this research is to efficiently analyze certain data provided and to see if a useful trend can be observed as a result. This trend can be used to analyze certain probabilities. There are three main pieces of data which are being analyzed in this research: The value for δ of the call and put option, the %B value of the stock, and the amount of time until expiration of the stock option. The %B value is the most important. The purpose of analyzing the data is to see the relationship between the variables and, given certain values, what is the probability the trade makes money. This result will be used in finding the probability certain trades make money over a period of time. Since options are so dependent on probability, this research specifically analyzes stock options rather than stocks themselves. Stock options have value like stocks except options are leveraged. The most common model used to calculate the value of an option is the Black-Scholes Model [1]. There are five main variables the Black-Scholes Model uses to calculate the overall value of an option. These variables are θ, δ, γ, v, and ρ. The variable, θ is the rate of change in price of the option due to time decay, δ is the rate of change of the option’s price due to the stock’s changing value, γ is the rate of change of δ, v represents the rate of change of the value of the option in relation to the stock’s volatility, and ρ represents the rate of change in value of the option in relation to the interest rate [2]. In this research, the %B value of the stock is analyzed along with the time until expiration of the option. All options have the same δ. This is due to the fact that all the options analyzed in this experiment are less than two months from expiration and the value of δ reveals how far in or out of the money an option is. The machine learning technique used to analyze the data and the probability is support vector machines. Support vector machines analyze data that can be classified in one of two or more groups and attempts to find a pattern in the data to develop a model, which reliably classifies similar, future data into the correct group. This is used to analyze the outcome of stock options. / Dissertation/Thesis / Masters Thesis Computer Science 2015

BACKGROUND - Bipolar disorder has been postulated as an explanation for King John's inconsistencies of leadership and vagaries of character. Changes in activity, matching those in mood, are core features of the condition. METHOD - A measure of King John's activity was derived from his travelling itinerary. Change Point Analysis (CPA) was used to detect significant changes in that travelling activity and from them, to identify clinically compliant, high and low, activity time periods. The results were tested against an alternative mathematical model (Bollinger Bands™), three alternative parameters and two comparator itineraries (familial & non-familial). Using primary historical sources and published analyses, bipolar symptoms were identified and their temporal relationship to the ICD-10 compliant CPA periods evaluated. The influence of circumstances was also evaluated using primary sources and a representative sequential sample (1200-1204). RESULTS - CPA identified 83 periods of changed travelling activity. These changes were mathematically independent of the availability of the historical sources that underpin the itinerary. From these, 37 high and 22 low periods complied with current diagnostic guidelines and demonstrated descriptive and statistical similarities to those found in the bipolar literature. Analyses using alternative mathematical modelling and different parameters showed similar changes; analyses of comparator itineraries showed a possible familial trait. Of the 17 bipolar symptoms identified, all were found in CPA periods of appropriate polarity. Of the 23 sequential periods, 10 showed evidence of behaviour that was difficult to attribute to circumstances. CONCLUSIONS & OUTCOMES - The pattern of changes in King John's activity are highly suggestive of bipolar disorder with primary historical sources describing synchronous bipolar behaviour. This may alter our understanding both of King John and of Magna Carta. Change Point Analysis merits greater consideration when analysing time based data, as does the use of activity as an objective marker of human behaviour.

該篇文章中提出一個新的交易方式：條件機率交易模型conditional probability trading model。 這個模型應用了三個主要的基本假設： （1）總體經濟因子和股價指數間有相關性。因此可以透過總經指標來衡量股市應有的合理價位。 （2）股價具有回歸均數的特質。亦即股價一旦過度偏離基本價值，理論上會傾向回復到基本價值之上。 （3）股價指數相對於基本價值線的距離，將會影響偏態係數的大小。 根據以上三個性質，試圖建構出一個能夠捕捉股價指數變動的模型，並用以進行交易模擬，觀察其是否能獲取正報酬。 / The trading strategy, conditional probability trading model(CPTM), is presented in this article. We’ve tried to develop a new trading strategy which is built up by the combination of the properties which includes 1)the relationship between macroeconomic factors and stock market. 2) mean reversion and 3) conditional skewness. The conclusion implies that we may successfully find out a method to combine fundamental and technical analysis, if this method is proved effective. The former hypothesis is assumed that the different level of stock market index may stand for a specific condition of macroeconomic environment. Meanwhile, a better fundamental economic condition could reasonably create a higher stock market index, vice versa. By observing the fundamental value, we can figure out the market ,currently, is over-priced or under-priced. Next, we construct a trading model which is graphed like Bollinger bands. According to specific rules, it provides buying or selling signals. In some special situations, it can also forecast the turning points of the stock market precisely. 3) Skewness also plays a very important role in CPTM, because one of the hypothesis assumes that overpriced /underpriced stock market probably accompanies with left-skewed / right-skewed distribution of daily stock return. The hypothesis of dynamically adjusted skewness implies the concept that over-priced/under-priced stock market has higher propensity to decline/rise. To judge the trading timing is the core value in this model.

Cette thèse propose des approches probabilistes pour améliorer et optimiser un des instruments les plus populaires de l'analyse technique, les bandes de trading. Les parties I et II se concentrent sur l'optimisation des composantes des bandes de trading: ligne centrale (représentée par la moyenne mobile) et lignes des bandes. La partie III est dédiée à l'amélioration du processus de prise de décision. Dans la partie I on propose d'utiliser le krigeage, une approche géostatistique, pour l'optimisation des poids des moyennes mobiles. Le krigeage permet d'obtenir l'estimateur optimal, qui incorpore les caractéristiques statistiques des données. Contrairement aux méthodes classiques, qui sont utilisées en finance, celle ci peut être appliquée aux données échantillonnées à maille régulière ou irrégulière. La partie II propose une méthode, basée sur la transformation des données en une variable normale, qui permet de définir les valeurs extrêmes et en conséquence les valeurs des bandes sans imposition de contraintes sur la distribution des résidus. Enfin, la partie III présente l'application des méthodes de krigeage disjonctif , une autre méthode géostatistique, pour les décision plus informative sur le timing et le type de position. Le krigeage disjonctif permet d'estimer les probabilités que certain seuils seront atteints dans le futur. Les résultats expérimentaux prouvent que les techniques proposées sont prometteuses et peuvent être utilisées en pratique.

In security markets, the stock price movements are closely linked to the market information. For example, the subprime mortgage triggered a global financial crisis in 2007. Drops occurred in virtually every stock market in the world. After the Federal Reserve took several steps to address the crisis, the stock markets have been gradually stable. Reaction of the traders to the arrival information results in different patterns of the stock price movements. Thus pattern matching is an important subject in future movement prediction, rule discovery and computer aided diagnosis. In this research, we propose a pattern matching procedure to seize the similar stock price movements of two listed companies during one day. First, the algorithm of searching the longest common subsequence is introduced to sieve out the time intervals where the two listed companies have the same integrated volatility levels and price rise/drop trends. Next we transform the raw price data in the found matching time periods to the Bollinger Band Percent data, then use the power spectrum to extract low frequency components. Adjusted Pearson chi-squared tests are performed to analyze the similarity of the price movement patterns in these periods. We perform the study by simulation investigation first, then apply the procedure to empirical analysis of high frequency transaction data of NYSE.

The thesis analyzes the network traffic on a router with open source firmware. First is chosen a software platform, based on compatibility with available equipment. Then are assessed properties necessary for the development of custom applications. Support for various programming languages provided by the SDK, development environment and the available modules and libraries, for working with network interface. Based on these factors is then chose method to realize the program. He is implemented on the OpenWRT firmware in C / C + + using network library pcap. These funds are used to capture and analyze network traffic. Obtained data are processed using methods of technical analysis, namely on the basis of moving averages, Stochastic oscillator and Bollinger bands. Based on results of these methods are generated and verified estimates of traffic. They are based on linear extrapolation, simplified for fixed intervals. The validity of each method is verified on base of the estimated value. Method is verified if estimated value of the traffic volume is in the Bollinger band, which is given by the standard deviation. Each method is tested several times in real traffic with different input parameters. Then is evaluated the influence of parameters on the error rate of methods. Individual methods are compared and evaluated based on the behavior in different scenarios and based on the average relative error.

This thesis deals with the automatization and comparison of two different strategies for the forex markets, based on the indicator, one from the tools of technical analysis, called Bollinger Bands. Both strategies are first optimized and then compared. Automatization of strategies will be implemented by? using the Meta Quotes Language for MetaTrader broker and its testing will be done on historical data. The goal with this thesis is the operational objective application of the better strategy in the environment of real market.