No description available.

No description available.

An original approach in microwave optimization, namely, a neural network procedure combined with the full-wave 3D electromagnetic simulator QuickWave-3D implemented a conformal FDTD method, is presented. The radial-basis-function network is trained by simulated frequency characteristics of S-parameters and geometric data of the corresponding system. High accuracy and computational efficiency of the procedure is illustrated for a waveguide bend, waveguide T-junction with a post, and a slotted waveguide as a radiating element.

The stomatal network in plants is a well-characterized biological system that hypothetically solves the constrained optimization problem of maximizing CO2 uptake from the air while constraining evaporative water loss during the process of photosynthesis. There are numerous such constrained optimization problems present in the real world as well as in computer science. This thesis work attempts to solve one such constrained optimization problem in a distributed manner by taking a cue from the dynamics of stomatal networks. The problem considered here is Dynamic Thermal Management (DTM) in a multi-processing element system in computing. There have been several approaches in the past that tried to solve the problem of DTM by varying the frequency of operation of blocks in the computing system. The selection of frequencies for DTM such that overall performance is maximized while temperature is constrained is a non-deterministic polynomial-time (NP) hard problem. In this thesis, a distributed approach to solve the problem of DTM using a cellular neural network is proposed. A cellular neural network is used to mimic the stomatal network with slight variations based on the problem considered.

The determination of economic control charts and the determination of specification limits with minimum cost are two different research topics. In this study, we first combine the design of economic control charts and the determination of specification limits to maximize the expected profit per unit time for the smaller the better quality variable following the gamma distribution. Because of the asymmetric distribution, we design the EWMA control chart with asymmetric control limits. We simultaneously determine the economic EWMA control chart and upper specification limit with maximum expected profit per unit time. Then, extend the approach to determine the economic variable sampling interval EWMA control chart and upper specification limit with maximum expected profit per unit time. In all our numerical examples of the two profit models, the optimum expected profit per unit time under inspection is higher than that of no inspection. The detection ability of the EWMA chart with an appropriate weight is always better than the X-bar probability chart. The detection ability of the VSI EWMA chart is also superior to that of the fixed sampling interval EWMA chart. Sensitivity analyses are provided to determine the significant parameters for the optimal design parameters and the optimal expected profit per unit time.

Σκοπός αυτής της διπλωματικής είναι να παρουσιάσει τη μεθοδολογία της Data Envelopment Analysis, μιας τεχνικής σύγκρισης οργανισμών με απώτερο σκοπό τη βελτιστοποίηση της λειτουργίας τους και τη μέτρηση της αποδοτικότητας τους. Γενικά οι μέθοδοι της ΠΕΑ χρησιμοποιούνται ως εργαλείο ώστε να αντιληφθούμε καλυτέρα και να αναλύσουμε το πώς κατανέμονται οι πόροι μιας επιχείρησης και πως αυτοί συνεισφέρουν στην παραγωγή της. Επιπρόσθετα, έχουν ως σκοπό να μεγιστοποιήσουν την απόδοση της επιχείρησης είτε περιορίζοντας τους πόρους της διατηρώντας το παραγόμενο προϊόν σταθερό είτε ελαχιστοποιώντας το παραγόμενο προϊόν διατηρώντας τους πόρους σταθερούς. Προκειμένου να μελετηθεί μια μονάδα απόφασης διαχωρίζεται σε «εισόδους» και «εξόδους». Όταν μιλάμε για εισόδους της υπό μελέτης μονάδας εννοούμε τους αναγκαίους πόρους που χρειάζεται για να λειτουργήσει ενώ αντίστοιχα ως εξόδους αναφέρουμε τα παραγόμενα προϊόντα ή υπηρεσίες που προσφέρει. Για παράδειγμα, ως είσοδοι σε τραπεζικά υποκαταστήματα μπορεί να θεωρηθούν τα λειτουργικά κόστη του ακινήτου και το προσωπικό ενώ ως έξοδοι το σύνολο των χρηματικών συναλλαγών που πραγματοποιούνται ή ο αριθμός των πελατών που έχουν συνάψει συνεργασία με το υποκατάστημα αυτό. Παρουσιάζεται αρχικά το μοντέλο CCR που είναι το βασικότερο ανάμεσα στις μεθόδους της DEA (παρουσιάστηκε το 1978 από τους Charnes, Cooper και Rhodes). Παρατίθεται η υπολογιστική διαδικασία του μοντέλου ΕΟΚ καθώς και μία επέκταση του με την χρήση του δυϊκού προβλήματος το οποίο υπερτερεί έναντι του πρωτεύοντος σε ταχύτητα επίλυσης σε μεγάλο αριθμό μονάδων απόφασης καθώς επίσης και στο εύρος λύσεων του προβλήματος. Το μοντέλο CCR καθώς και οι επεκτάσεις του στηρίχτηκαν στον ορισμό των σταθερών οικονομιών κλίμακας δηλαδή θα πρέπει να ισχύει ότι εάν μια δράση (x,y) είναι εφικτή, τότε για κάθε θετικό αριθμό t, η δράση (tx,ty) είναι επίσης εφικτή. Έτσι, αν αποδώσουμε γραφικά την αποδοτικότητα όλων των μονάδων απόφασης και σχεδιάσουμε το σύνορο αποδοτικότητας, αυτό θα αποτελείται από ευθύγραμμα τμήματα με ακμές τις μονάδες απόφασης. Το επόμενο μοντέλο που παρουσιάζεται είναι αυτό των Banker, Charnes και Cooper (BBC) όπου η κύρια διάφορα του με το προηγούμενο έγκειται στο γεγονός ότι το σύνολο παραγωγικότητας είναι το κυρτό σύνολο των σημείων που απεικονίζουν τις μονάδες απόφασης (και όχι τα ευθύγραμμα τμήματα τους). Κοινό χαρακτηριστικό και των δύο παραπάνω μοντέλων είναι ότι κάθε φορά στην ανάλυση των δεδομένων πρέπει να εστιάσουμε είτε στην ελαχιστοποίηση των εισόδων είτε στην μεγιστοποίηση των εξόδων για να εξάγουμε συμπεράσματα. Τα προσθετικά μοντέλα που παρουσιάζονται στη συνέχεια δεν κάνουν αυτόν τον διαχωρισμό καθώς στηρίζονται στην ελαχιστοποίηση της περίσσειας πόρων εισόδου και την ταυτόχρονη μεγιστοποίηση των παραγόμενων εξόδων. Επιπρόσθετα, πλεονέκτημα των προσθετικών μοντέλων είναι η ανάλυση αρνητικών δεδομένων κάτι που δεν ήταν εφικτό από τα προηγούμενα μοντέλα. Παρουσιάζεται, επίσης, μια επέκταση του προσθετικού μοντέλου όπου η μέτρηση της αποδοτικότητας δεν επηρεάζεται από τυχόν διαφορές στις μονάδες μέτρησης ανάμεσα στις εξόδους και τις εισόδους. Τέλος περιγράφεται η ανάλυση ευαισθησίας που είναι μία σημαντική παράμετρος των μεθόδων της DEA καθώς δίνει την δυνατότητα σε κάποιον να μελετήσει τις διαφοροποιήσεις όταν εισάγονται η διαγράφονται μονάδες λήψης αποφάσεων η όταν εισάγονται η διαγράφονται είσοδοι και έξοδοι σε ένα πρόβλημα. / The purpose of this thesis is to present the methodology of Data Envelopment Analysis, a technique to compare organizations with a view to optimizing the operation and measurement of their profitability. Generally, methods of DEA are used as a tool to better understand and analyze how resources are distributed and how each one contributes to company’s production. Additionally, they are designed to maximize the performance of business by limiting its resources while maintaining the output constant or by minimizing the product obtained by maintaining the resources constant. The unique characteristics of every decision making unit are "inputs" and "outputs". Inputs of a unit correspond to the resources needed for the company to operate and outputs correspond to the products or services offered. For example, inputs in bank branches can be considered all the operating costs of the property and the personnel occupied and us outputs all financial transactions carried out or the whole number of customers that have made transactions with a particular branch. Initially the CCR model is presented as it is considered to be the very first method of DEA (firstly introduced by Charnes, Cooper and Rhodes). The whole process of the CCR model is presented and also an extension and the use of the dual problem that outweighs the computational speed of the primary model in solving a large number of decision points as well as the range of solutions to the problem. The CCR model and its extensions are based on the definition of constant economies of scale which can be expressed as if an action (x, y) is feasible, then for each positive number t, the action (tx, ty) is also feasible. Thus, if we depict the performance of every decision making unit in a single graph with their corresponding performance, then the efficient frontier consists of segments that have decision making units in each edge The next model presented is that of Banker, Charnes and Cooper (BBC) where the main difference with the previous lies in the fact that total productivity is the convex set of points that reflects the decision making units (and not their segments). A common feature of both these models is that each time the data analysis should focus either on minimizing inputs or on maximizing outputs to come over a conclusion. The additive models presented does not make this distinction as they are based on the minimization of the excess resources of inputs and simultaneously on the maximization of produced outputs. Additionally, a competitive advantage of the additive model is the analysis of negative data which was not possible with previous models. An extension of the additive model is presented where the measurement of efficiency is not affected by any differences in units between the inputs and outputs. Finally, the sensitivity analysis is described as an important parameter of DEA’s methods as it analyses the differences in production when a decision making unit is imported or deleted or when inputs and outputs are being inserted or deleted in a problem set.

This diploma thesis deals with the modeling of planar antennas with special superstrates in the CST Microwave Studio. Attention is given to the electromagnetic bandgap (EBG) substrates. Firstly, the working principle of these special substrates and generally physical phenomena accompanying electromagnetic waves propagation in a periodic medium are analyzed. By modeling of basic EBG structures in CST their dispersion diagrams were obtained and afterwards compared to one another. The object of the second part of this thesis was modeling of a chosen antenna in CST. An Antenna placed first on the conventional and then on the EBG substrate - in both cases with special superstrates - is analyzed and compared to each other. In the third part of this thesis, the particle swarm optimization (PSO) technique was implemented in CST (VBA language), and was applied to the original design of the chosen antenna. In the final part of this thesis, the optimized antenna was modeled and analyzed in ANSOFT HFSS, and the results from both simulation programs are compared to each other.

Power system state estimation (PSSE) is an energy management system function responsible for the computation of the most likely values of state variables viz., bus voltage magnitudes and angles. The state estimation is obtained within a network at a given instant by solving a system of mostly non-linear equations whose parameters are the redundant measurements, both static such as transformer/line parameters and dynamic such as, status of circuit breakers/isolators, transformer tap positions, active/reactive power flows, generator active/reactive power outputs etc. PSSE involves solving an over determined set of nonlinear equations by minimizing a weighted norm of the measurement residuals. Typically, the L1 and L2 norms are employed. The use of L2 norm leads to state estimation based on the weighted least squares (WLS) criterion. This method is known to exhibit efficient filtering capability when the errors are Gaussian but fails in the case of presence of bad data. The method of hypothesis testing identification can be incorporated into the WLS estimator to detect and identify bad data. Nevertheless, it is prone to failure when the measurement is a leverage point. On the other hand state estimation based on the weighted least absolute value (WLAV) criterion using L1 norm, has superior bad data suppression capability. But it also fails in rejecting bad data measurements associated with leverage points. Leverage points are highly influential measurements that attract the state estimator solution towards them. Consequently, much research effort has focused recently, on producing a LAV estimator that remains robust in the presence of bad leverage measurements. This problem has been addressed in the thesis work. Two methods, which aims development of robust estimator that are insensitive to bad leverage points, have been proposed viz., (i) The objective function used here is obtained by linearizing L2 norm of the error function. In addition to the constraints corresponding to measurement set, constraints corresponding to bounds of state variables are also involved. Linear programming (LP) optimization is carried out using upper bound optimization technique. (ii) A hybrid optimization algorithm which is combination of”upper bound optimization technique” and ”an improved algorithm for discrete l1 linear approximation”, to restrict the state variables not to leave the basis during optimization process. Linear programming optimization, with bounds of state variables as additional constraints is carried out using the proposed hybrid optimization algorithm. The proposed state estimator algorithms are tested on 24-bus EHV equivalent of southern power network, 36-bus EHV equivalent of western grid, 205-bus interconnected grid system of southern region and IEEE-39 bus New England system. Performances of the proposed two methods are compared with the WLAV estimator in the presence of bad data associated with leverage points. Also, the effect of bad leverage measurements on the interacting bad data, which are non-leverage, has been compared. Results show that proposed state estimator algorithms rejects bad data associated with leverage points efficiently.

近年來有許多研究發現，適應性管制圖在偵測製程或產品幅度偏移時的速度比傳統的舒華特管制圖來的快，許多文獻也討論到利用適應性管制技術同時監控製程的平均數和變異數。隨著科技的發達，許多產品在製造上更加精密，現今普遍使用的固定參數管制圖並無法有效率的偵測出製程失控，導致巨大的成本損失。為了改善現有管制圖的偵測效率與有效控制製程失控下的損失，我們提出了三種適應性加權損失管制圖，包括變動抽樣間隔(VSI)、變動樣本數與抽樣間隔(VSI)、變動管制參數(VP)來偵測單一製程與兩相依製程的平均數和變異數。採用製程發生變動後到管制圖偵測出異常訊息所需的平均時間(AATS)與所需的總觀測數(ANOS)來衡量管制圖的偵測績效，並利用馬可夫鏈推導計算得之。從數值分析中發現，適應性加權損失管制圖在「偵測小偏移幅度時的偵測效率」與「成本的控制」明顯比傳統管制圖表現的更好，再加上每一個製程僅需採用單一管制圖，對使用者也較為簡便並且容易理解，因此適應性加權損失管制圖在實務上是值得被推薦使用的。 / Recent research has shown that control charts with adaptive features detect process shifts faster than traditional Shewhart charts. In this article, we propose three kinds of adaptive weighted loss (WL) control charts, variable sampling intervals (VSI) WL control charts , variable sample sizes and sampling intervals (VSSI) WL control charts and variable parameters (VP) WL control charts, to monitor the target and variance on a single process step and two dependent process steps simultaneously. These adaptive WL control charts may effectively distinguish which process step is out-of-control. We use the Markov chain approach to calculate the adjusted average time to signal (AATS) and average number of observations to signal (ANOS) in order to measure the performance of the proposed control charts. From the numerical examples and data analyses, we find the adaptive WL control charts have better detection abilities and performance than fixed parameters (FP) WL control charts and FP Z(X-bar)-Z(Sx^2) and Z(e-bar)-Z(Se^2) control charts. We also proposed the optimal adaptive WL control charts using an optimization technique to minimize AATS when users cannot specify the values of the variable parameters. In addition, we discuss the impact of misusing weighted loss of outgoing quality control chart. In conclusion, using a single chart to monitor a process is inherently easier than using two charts. The WL control charts are easy to understand for the users, and have better performance and detection abilities than the other charts, thus, we recommend the use of WL control charts in the real industrial process.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Sistemas estruturais em suas variadas aplicações incluindo-se veículos espaciais, automóveis e estruturas de engenharia civil tais como prédios, pontes e plataformas off-shore, acumulam dano durante suas vidas úteis. Em muitas situações, tal dano pode não ser visualmente observado. Do ponto de vista da segurança e da performance da estrutura, é desejável monitorar esta possível ocorrência, localizá-la e quantificá-la. Métodos de identificação de sistemas, que em geral, são classificados numa categoria de Técnicas de Avaliação Não-Destrutivas, podem ser utilizados para esta finalidade. Usando dados experimentais tais como frequências naturais, modos de vibração e deslocamentos estáticos, e um modelo analítico estrutural, parâmetros da estrutura podem ser identificados. As propriedades estruturais do modelo analítico são modificadas de modo a minimizar a diferença entre os dados obtidos por aquele modelo e a resposta medida. Isto pode ser definido como um problema inverso onde os parâmetros da estrutura são identificados. O problema inverso, descrito acima, foi resolvido usando métodos globais de otimização devido à provável presença de inúmeros mínimos locais e a não convexidade do espaço de projeto. Neste trabalho o método da Evolução Diferencial (Differential Evolution, DE) foi utilizado como ferramenta principal de otimização. Trata-se de uma meta-heurística inspirada numa população de soluções sucessivamente atualizada por operações aritméticas como mutações, recombinações e critérios de seleção dos melhores indivíduos até que um critério de convergência seja alcançado. O método da Evolução Diferencial foi desenvolvido como uma heurística para minimizar funções não diferenciáveis e foi aplicado a estruturas planas de treliças com diferentes níveis de danos. / Structural systems in a variety of applications including aerospace vehicles, automobiles and civil engineering structures such as tall buildings, bridges and offshore platforms, accumulate damage during their service life. In several situations, such damage may not be visually observable. From the standpoint of both safety and performance, it is desirable to monitor the occurrence, location and extent of such damage.System identification methods, which may be classified in a general category of nondestructive evaluation techniques, can be employed for this purpose. Using experimental data, such as eigenmodes, eigenvectors and static displacements, and an analytical structural model, parameters of the structures can be identified. The approach used in the present work is one where the structural properties of the analytical model are varied to minimize the difference between the analytically predicted and empirically measured response. This is an inverse problem where the structural parameters are identified. In this work a reduced number of vibration modes were used as the measured response. For the damage assessment problem a close analytical model of the structural system is available and the model of the damaged structure will be identified. Damage will be represented by a reduction in the elastic stiffness properties of the structure.The problem described above was solved using global methods of optimization due to the fact that depending on the number of variables or the location of damage the resulting design space is nonconvex presenting several local minima. In the present work, the Differential Evolution Optimization Technique (DE) was used. It is a metaheuristic inspired by a population of solutions that is successively updated by arithmetic operations such as mutation and recombination, until convergence. The approach was applied to simple truss structures with different levels of damage.