With recent developments in power conversion technologies and market trends that are driving those technologies toward further miniaturization and greater integration, the need for verifying an empirically based modeling methodology for proprietary power converters such as Power Supply on Chip (PwrSoC) products has risen significantly. This need motivates the investigation of black-box models which require little or no knowledge of the internal workings of a system, for those areas of industry adopting PwrSoC technology as a point-of-load solution. This thesis reports a black-box modeling method tailored to accommodate but not limited to the requirements of a specific commercially available PwrSoC technology.

A key cryptographic research interest is developing an automatic, black-box method to provide a relative security strength measure for symmetric ciphers, particularly for proprietary cyber-physical systems (CPS) and lightweight block ciphers. This thesis work extends the work of the recently-developed neural cryptanalysis method, which trains neural networks on a set of plaintext/ciphertext pairs to extract meaningful bitwise relationships and predict corresponding ciphertexts given a set of plaintexts. As opposed to traditional cryptanalysis, the goal is not key recovery but achieving a mimic accuracy greater than a defined base match rate. In addition to reproducing tests run with the Data Encryption Standard, this work applies neural cryptanalysis to round-reduced versions and components of the SIMON/SPECK family of block ciphers and the Advanced Encryption Standard. This methodology generated a metric able to rank the relative strengths of rounds for each cipher as well as algorithmic components within these ciphers. Given the current neural network suite tested, neural cryptanalysis is best-suited for analyzing components of ciphers rather than full encryption models. If these models are improved, this method presents a promising future in measuring the strength of lightweight symmetric ciphers, particularly for CPS. / Master of Science / Cryptanalysis is the process of systematically measuring the strength of ciphers, algorithms used to secure data and information. Through encryption, a cipher is applied to an original message or plaintext to generate muddled message or ciphertext. The inverse of this operation, translating ciphertext back into plaintext, is decryption. Symmetric ciphers only require one shared secret key that is used during for both encryption and decryption. Machine learning is a data analysis method that automates computers to learn certain data properties, which can be used to predict outputs given a set of inputs. Neural networks are one type of machine learning used to uncover relationships, chaining a series of nodes together that individually perform some operations to determine correlations. The topic of this work is neural cryptanalysis, a new approach to evaluate cipher strength relying on machine learning. In this method, the goal is to "learn" the ciphers, using machine learning to predict what the ciphertext will be for an inputted plaintext. This is done by training the networks on plaintext/ciphertext pairs to extract meaningful relationships. If a cipher is easier to predict, it is easier to crack and thus less secure. In this work, neural cryptanalysis was applied to different real-world symmetric ciphers to rank their relatively security. This technique worked best on analyzing smaller components of the cipher algorithms rather than the entire cipher, as the ciphers were complex and the neural networks were simpler.

Characterization and modeling of devices at high drive levels often requires specialized equipment and measurement techniques. Many large-signal devices will never have traditional nonlinear models because model development is expensive and time-consuming. Due to the complexity of the device or the size of the application market, nonlinear modeling efforts may not be cost effective. Scattering parameters, widely used for small-signal passive and active device characterization, have received only cursory consideration for large-signal nonlinear device characterization due to technical and theoretical issues. We review the theory of S-parameters, active device characterization, and previous efforts to use S-parameters with large-signal nonlinear devices. A robust, calibrated vector-measurement system is used to obtain device scattering parameters as a function of drive level. The unique measurement system architecture allows meaningful scattering parameter measurements of large-signal nonlinear devices, overcoming limitations reported by previous researchers. A three-port S-parameter device model, with a nonlinear reflection coefficient terminating the third port, can be extracted from scattering parameters measured as a function of drive level. This three-port model provides excellent agreement with device measurements across a wide range of drive conditions. The model is used to simulate load-pull data for various drive levels which are compared to measured data. / Master of Science

Die Elektronisierung der Finanzmärkte ist in den letzten Jahren weit vorangeschritten. Praktisch jede Börse verfügt über ein elektronisches Handelssystem. In diesem Kontext beschreibt der Begriff Algorithmic Trading ein Phänomen, bei dem Computerprogramme den Menschen im Wertpapierhandel ersetzen. Sie helfen dabei Investmententscheidungen zu treffen oder Transaktionen durchzuführen. Algorithmic Trading selbst ist dabei nur eine unter vielen Innovationen, welche die Entwicklung des Börsenhandels geprägt haben. Hier sind z.B. die Erfindung der Telegraphie, des Telefons, des FAX oder der elektronische Wertpapierabwicklung zu nennen. Die Frage ist heute nicht mehr, ob Computerprogramme im Börsenhandel eingesetzt werden. Sondern die Frage ist, wo die Grenze zwischen vollautomatischem Börsenhandel (durch Computer) und manuellem Börsenhandel (von Menschen) verläuft. Bei der Erforschung von Algorithmic Trading wird die Wissenschaft mit dem Problem konfrontiert, dass keinerlei Informationen über diese Computerprogramme zugänglich sind. Die Idee dieser Dissertation bestand darin, dieses Problem zu umgehen und Informationen über Algorithmic Trading indirekt aus der Analyse von (Fonds-)Renditen zu extrahieren. Johannes Gomolka untersucht daher die Forschungsfrage, ob sich Aussagen über computergesteuerten Wertpapierhandel (kurz: Algorithmic Trading) aus der Analyse von (Fonds-)Renditen ziehen lassen. Zur Beantwortung dieser Forschungsfrage formuliert der Autor eine neue Definition von Algorithmic Trading und unterscheidet mit Buy-Side und Sell-Side Algorithmic Trading zwei grundlegende Funktionen der Computerprogramme (die Entscheidungs- und die Transaktionsunterstützung). Für seine empirische Untersuchung greift Gomolka auf das Multifaktorenmodell zur Style-Analyse von Fung und Hsieh (1997) zurück. Mit Hilfe dieses Modells ist es möglich, die Zeitreihen von Fondsrenditen in interpretierbare Grundbestandteile zu zerlegen und den einzelnen Regressionsfaktoren eine inhaltliche Bedeutung zuzuordnen. Die Ergebnisse dieser Dissertation zeigen, dass man mit Hilfe der Style-Analyse Aussagen über Algorithmic Trading aus der Analyse von (Fonds-)Renditen machen kann. Die Aussagen sind jedoch keiner technischen Natur, sondern auf die Analyse von Handelsstrategien (Investment-Styles) begrenzt. / During the last decade the electronic trading on the stock exchanges advanced rapidly. Today almost every exchange is running an electronic trading system. In this context the term algorithmic trading describes a phenomenon, where computer programs are replacing the human trader, when making investment decisions or facilitating transactions. Algorithmic trading itself stands in a row of many other innovations that helped to develop the financial markets technologically (see for example telegraphy, the telephone, FAX or electronic settlement). Today the question is not, whether computer programs are used or not. The question arising is rather, where the border between automatic, computer driven and human trading can be drawn. Conducting research on algorithmic trading confronts scientists always with the problem of limited availability of information. The idea of this dissertation is to circumnavigate this problem and to extract information indirectly from an analysis of a time series of (fund)-returns data. The research question here is: Is it possible to draw conclusions about algorithmic trading from an analysis of (funds-)return data? To answer this question, the author develops a complete definition of algorithmic trading. He differentiates between Buy-Side and Sell-Side algorithmic trading, depending on the functions of the computer programs (supporting investment-decisions or transaction management). Further, the author applies the multifactor model of the style analysis, formely introduced by Fung and Hsieh (1997). The multifactor model allows to separate fund returns into regression factors that can be attributed to different reasons. The results of this dissertation do show that it is possible to draw conclusions about algorithmic trading out of the analysis of funds returns. Yet these conclusions cannot be of technical nature. They rather have to be attributed to investment strategies (investment styles).

Názov práce: Evoluční algoritmy a aktivní učení Autor: Jakub Repický Katedra: Katedra teoretické informatiky a matematické logiky Vedúci diplomovej práce: doc. RNDr. Ing. Martin Holeňa, CSc., Ústav informa- tiky, Akademie věd České republiky Abstrakt: Vyhodnotenie ciel'ovej funkcie v úlohách spojitej optimalizácie často do- minuje výpočtovej náročnosti algoritmu. Platí to najmä v prípade black-box fun- kcií, t. j. funkcií, ktorých analytický popis nie je známy a ktoré sú vyhodnocované empiricky. Témou urýchl'ovania black-box optimalizácie s pomocou náhradných modelov ciel'ovej funkcie sa zaoberá vel'a autorov a autoriek. Ciel'om tejto dip- lomovej práce je vyhodnotit' niekol'ko metód, ktoré prepájajú náhradné modely založené na Gaussovských procesoch (GP) s Evolučnou stratégiou adaptácie ko- variančnej matice (CMA-ES). Gaussovské procesy umožňujú aktívne učenie, pri ktorom sú body pre vyhodnotenie vyberané s ciel'om zlepšit' presnost' modelu. Tradičné náhradné modely založené na GP zah'rňajú Metamodelom asistovanú evolučnú stratégiu (MA-ES) a Optimalizačnú procedúru pomocou Gaussovských procesov (GPOP). Pre účely tejto práce boli oba prístupy znovu implementované a po prvý krát vyhodnotené na frameworku Black-Box...

En kulturskola är inte ett skyltfönster för barnens talang utan en kreativ verkstad för att utvecklas. Detta har jag tagit fasta på och har en idé om en kulturskola där större delen av skolan är vikt till barnens trygghet. De vuxna har sin plats och resten av byggnaden är barnens. Här ska blyga kunna öva i trygghet och de som vill spela ut hela sin repertoar har möjlighet till det. Skolan ska också kunna vara en plats att hänga på någon timme innan sin lektion. Gestaltningsmässigt har skolan här ett öppet foajéplan som är semioffentlig. Caféet är öppet för allmänheten och kan användas för utställningar, föreläsningar och liknande. Men denna yta är också den som är de vuxnas. Kommer du med ditt barn så är det här du får vänta medan barnet springer in och gör sitt. Resten av foajéplanet är en flexibel yta som egentligen kan programmeras lite hur som helst. Uppåt i huset finns en yta för barn, som ett väntrum, där de kan hänga innan sin lektion. Uppåt finns också lektionssalar. Blandad verksamhet för att blanda barnen.  Den nedre delen av huset är nästan som ett helt annat hus. Här finns verksamhetslokaler samt flertalet av de servicefunktioner som måste finnas. Ytan att vistas på är här begränsad då det inte är tänkt att man ska uppehålla sig här mellan lektionerna. Som en bärande idé har jag fört med mig forskning som visar på hur man kan bygga bort mobbning. Huset har inga långa dolda korridorer och överallt kan lärare överse, utan att bevaka, alla utrymmen där barnen befinner sig. Med hörsel och syn kopplas hela huset samman genom principen att visuell och audiell kommunikation är trygghetens kärna. / A Culture school should not be a kids talent show room. It should be a creative shop for their own development. This is the starting point of my project. I have an idea of a culture school where the bigger part is for the children and only the children. A place to be safe. The shy kids should be able to practice in a safe environment and the more outspoken kids will have the opportunity to perform. This, normally a place you just spend a lesson at, should be a place to hang around after school. The entrance floor is a semi public floor with an café open for the public and with an area to have flexible purposes, maybe a show room one day and an open lecture the next. This area is the only area for the grown ups. When you pass through into the building you are in the world for the kids. The flexible entrance floor is accompanied with a ”half floor” entirely voided for the kids to hang at. Another floor up and two floors down you’ll find the rooms for different activities. The entire house is devoted to minimize bullying. No long corridors, a constant ability for teachers to watch the kids without being monitors and throughout the house you can hear, and almost see, everything.

Understanding how a system behaves when exposed to different scenarios is key when improvingand developing complex structures. The amount of different approaches is immense and variesfrom case to case. One of the simpler approaches is black-box modelling as it only targetsan input and output to a system, and not necessarily the mathematical interpretations. Fora nonlinear system such as a remote controlled weapon station, this approach is appropriate,as it allows to only focus on a certain scenario and the results obtained for that case. In thisstudy, a remote controlled weapon station is further investigated when exposed to disturbancesfrom a combat vehicle. The data obtained is simulated on a platform and the results are usedin Matlab to analyze and find the best model from these tests. A Hammerstein-Wiener modelwith nonlinear wavelet networks is deemed the best as it gives the most accurate representationof the station’s behavior. The results obtained are considered to be moderately accurate dueto its precision and should only be used as reference point, rather than being interpreted as atrue representation of the system. / Att förstå hur ett system beter sig när det utsätts för olika scenarier är viktigt när man skaförbättra och utveckla komplexa strukturer. Mängden olika tillvägagångssätt är näst intillobegränsad och varierar från fall till fall. Ett av de enklare tillvägagångssätten är "blackbox" modellering eftersom det bara riktar sig till in- och utsignal till ett system, och intenödvändigtvis de matematiska tolkningarna. För ett icke-linjärt system så som en fjärrstyrdvapenstation, är detta tillvägagångssätt lämpligt, eftersom det tillåter att bara fokusera på ettvisst scenario och de resultat som erhålls för det fallet. I denna studie undersöks en fjärrstyrdvapenstation när den utsätts för störningar från ett stridsfordon. Den erhållna datan simuleraspå en plattform och resultaten används i Matlab för att analysera och hitta den bästa modellenfrån dessa tester. En Hammerstein-Wiener-modell med icke-linjära wavelet-nätverk anses varaden bästa eftersom den ger den mest exakta representationen av stationens beteende. Deerhållna resultaten anses vara mediokra på grund av dess precision och bör endast användassom en referenspunkt, snarare än att tolkas som en sann representation av systemet.

In this thesis, black-box models describing the quadcopter system dynamics for attitude control have been estimated using closed-loop data. A quadcopter is a naturally unstable multiple input multiple output (MIMO) system and is therefore an interesting platform to test and evaluate ideas in system identification and control theory on. The estimated attitude models have been shown to explain the output signals well enough during simulations to properly tune a PID controller for outdoor flight purposes. With data collected in closed loop during outdoor flights, knowledge about the controller and IMU measurements, three decoupled models have been estimated for the angles and angular rates in roll, pitch and yaw. The models for roll and pitch have been forced to have the same model structure and orders since this reflects the geometry of the quadcopter. The models have been validated by simulating the closed-loop system where they could explain the output signals well. The estimated models have then been used to design attitude controllers to stabilize the quadcopter around the hovering state. Three PID controllers have been implemented on the quadcopter and evaluated in simulation before being tested during both indoor and outdoor flights. The controllers have been shown to stabilize the quadcopter with good reference tracking. However, the performance of the pitch controller could be improved further as there have been small oscillations present that may indicate a stronger correlation between the roll and pitch channels than assumed.

A linear model of an annealing furnace is developed using a black-box system identification approach, and used when testing three different control strategies to improve temperature control. The purpose of the investigation was to see if it was possible to improve the temperature control while at the same time  decrease the switching frequency of the  burners. This will lead to a more efficient process as well as less maintenance, which has both economic and environmental benefits. The estimated model has been used to simulate the furnace with both the existing controller and possible new controllers such as a split range controller and a model predictive controller (MPC). A split range controller is a control strategy which can be used when more than one control signal affect the output signal, and the control signals have different range. The main advantage with MPC is that it can take limitations and constraints into account for the controlled process, and with the use of integer programming, explicitly account for the discrete switching behavior of the burners. In simulation both new controllers succeed in decreasing the switching and the MPC also improved the temperature control. This suggest that the control of the furnace can be improved by implementing one of the evaluated controllers.

<p>The purpose of this thesis work was to develop an automatic fault detection system for surveillance of bearing temperature in hydropower turbines. The parameters used except the bearing temperature were cooling water temperature and cooling water flow. A simple static model based on data sampled every minute was developed to estimate the bearing temperature. Then a detector for detection of change in bearing temperature based on the CUSUM-algorithm was designed. Since the amount of data was very small the developed model was too uncertain to be used in a working system.</p><p>The designed fault detection system showed to work well for the available data. It is, however, recommended that the performance of the system should be evaluated using more data. Another model based on data sampled once every minute for at least a year has to be developed before the system can be fully evaluated. The results shown were:</p><p>• The fault detection system can discover fast and slow changes in bearing temperature.</p><p>• No false alarms were given for measuring faults and sensor faults of the types used in this thesis. If a measuring fault occurs for too long there will be an alarm.</p><p>The fault detection algorithm was also implemented in Delphi to be used in a working system over the Internet where for example trends and alarms will be presented.</p> / <p>Syftet med examensarbetet var att utveckla ett automatiskt feldetekteringssystem för övervakning av bärlagertemperaturen i vattenkraftturbiner. De ingående parametrarna förutom bärlagertemperaturen var kylvattentemperaturen och kylvattenflödet. En enkel statisk modell baserad på data samplat en gång per minut togs fram för att estimera bärlagertemperaturen. Därefter utvecklades en detektor för att upptäcka avvikelser i bärlagertemperaturen baserad på CUSUM-algoritmen. På grund av en för liten mängd data var den framtagna modellen alltför osäker för att kunna implementeras i ett fungerande system.</p><p>Det framtagna feldetekteringssystemet visade sig fungera bra för de data som fanns tillgängliga. Det är däremot rekommenderat att utvärdera systemets prestanda med längre dataserier. En ytterligare modell baserad på minutdata över ett år måste tas fram innan systemet kan fungera på riktigt. De resultat som erhölls var:</p><p>• Feldetekteringssystemet klarar av att upptäcka abrupta och långsamma avvikelser av bärlagertemperaturen.</p><p>• Inga falsklarm ges då det är enstaka mätfel eller givarfel av sådan typ som tagits upp i arbetet. Pågår ett mätfel alltför länge ges dock ett larm.</p><p>Feldetekteringsalgoritmen implementerades även i Delphi för att kunna användas i ett fungerande system över Internet där t.ex. trendkurvor och larmsignaler skall kunna presenteras.</p>