Problem Formulation. Problem setup: estimating the location of source A by analysing the signals recorded by the "Main" and "Spot" microphones (please refer to text for more details).
Problem Formulation. 3.2.1 Process and noise models
Problem Formulation. Five actors were introduced above. No matter if we call them organizations, institutions or simply parts of the different levels of a 'bureaucratic system'. The structure which they are part of resembles a living organism. Each of these actors could be described as a single body organ and its employees as the organ's cells. If the employees, human beings, do cooperate and communicate between each other, the organ works and operates. But this is not enough to keep the whole living organism alive. The indispensable condition lies in the mutual cooperation and 'communication' between all organs. If they cooperate, everything is more or less all right and the organism flourishes. On the other hand, divergences, malfunction or even total absence of cooperation leads to problems and if not treated, to death. We argue that in this case, communication between the actors has as pivotal role as in the above mentioned parallel with the living organism. We also believe that when it comes to people, the functional communication is a key basically to all problems. And since we as human beings do communicate all the time, it is impossible to avoid failures in communication. But as Xxxxxx, a Roman Stoic philosopher, said “Errare humamun est” (To err is human). Nevertheless, his idea further continues by words “sed in errare perserevare diabolicum” (but to persist in the error is diabolical). The aim of this thesis is therefore to explore what communication in the chosen issue looks like. How do the actors perceive the situation? Do they want to change the present state or do they feel satisfied with it? We have interviewed different people with different opinions and backgrounds in order to get an overview of the whole situation. How do they perceive their own roles and what are their opinions of the other actors? Do they feel their voice is being heard enough when cooperate and communicate with the other actors? What are their wishes or suggestions for the future? The following pages describe how their answers were processed, analyzed and connected with relevant theories in order to investigate the phenomenon of communication pertaining to this issue.
Problem Formulation. For the PAINLESS project, we propose a cooperative protocol over a multi-hop network with relays, where each relay has a buffer of finite size. The main contribution of this work is the investigation of a theoretical framework to analyse such cooperative networks in terms of outage probability and diversity gain. The protocol is based on the -hop my- opic DF coding strategy [13], where represents the maximum number of nodes that a transmitter can forward data concurrently. The received signals of each relay are stored in a buffer i of finite size i = min(, − + 1) which is used as a one-dimensional array with indexed elements, where the element i[], 1 ≤ ≤ i, refers to the -th most recently received signal. We assume that a signal at the receiver is successfully de- coded if the instantaneous signal-to-noise ratio (SNR) is not below a predefined threshold , otherwise an outage occurs. For this, a one-dimensional array i is introduced that in- dicates which of the received signals stored in the buffer i were successfully decoded. Therefore, the transmission of the decoded signals to the appropriate nodes is adapted according to the status of the arrays i. Each relay is activated by harvesting energy from a BS , which is used as a power bea- con, and uses its harvested energy for forwarding its decoded signals, as it is shown in Beacon S R1 R2 R3 D
3.1: Topology for 2-hop myopic DF strategy in a wireless network with three relays.
Fig. 3.1. For this, the TS technique is used [6], where for each time-slot the relays dedicate a portion of that time for EH and the rest of the time-slot for transferring the decoded signals. A relay can forward data only if its harvested energy is at least equal to a prede- fined threshold, otherwise it remains idle and stores the harvested energy for the next time-slot. Finally, for the analysis we consider independent and identically distributed (i.i.
Problem Formulation. Given the system model (1)-(2) and attacker model (3)-(4), design a key-agreement scheme between a plant’s actuator (hereafter referred to as the smart actuator or just actuator) and the controller such that: - The key-agreement is achieved by leveraging the asymmetry (4) in the system model knowledge (i.e., no cryptography schemes are explicitly used); - Let c 0, 1 n, sa 0, 1 n and e 0, 1 n be the binary keys of length n > 0 identified by the controller, smart actuator and Eve, respectively. Then, P (Kc = Ksa) ≈ 1 and P ( c = e) 1. In this correspondence, a solution to the above problem is given under the assumption that an unknown input observer for (1) can be defined to simultaneously estimate the state xk (namely xˆk) and the input signal uk (namely uˆk) from the sensor measurement yk. In what follows, the UIO algorithm is abstractly described by means of the following recursive UIO function: [uˆk−1, xˆk] = UIO(uˆk−2, xˆk−1, yk, ł) (5) where the pairs (uˆk−1, xˆk) and (uˆk−2, xˆk−1) define the available estimation at the time k and k — 1, respectively.
Problem Formulation. How does the lack of a Booklet of Technical Vocabulary impact on the interpretation and understanding of technical manuals in the First Course´s students in the specialization of Electricity at Alborada Technical and Industrial Senior High School in the school year 2013?
Problem Formulation. How does the lack of audiovisual resources affecting on teaching-learning process of English language at Dr. Xxxx Xxxxx Xxxxxxx Xxxxxx High School´s Eight Grade students of Basic General Education?
Problem Formulation. How does the lack of interactive audiovisual didactic resources influence in the teaching - learning of the English language in the students of ninth year of Basic Education at ¨EL TRIUNFO¨ High School during the school year 2011-2012
Problem Formulation. How does the lack of the application in the cooperative strategies influence the teaching-learning process on English language´s meaningful excellence and quality of the whole process in the English language acquisition?
Problem Formulation. In a typical classification problem, a training set of labelled examples is given. The training set can be described in a variety of languages, most frequently, as a collection of patterns denoted as S = (< x1 , y1 >,..., < xm , ym >) where xq ∈X is a vector of feature values charactering the pattern and y ∈{c1,..., ck } indicates the pattern’s class. Usually, it is assumed that the training set records are generated randomly and independently according to some fixed and unknown joint probability distribution D. Let Ω ={ M1,..., Mn } represent an ensemble of n classifiers. Mi is a classifier that can predict the class Mi ( xq ) of an observation xq. The problem of ensemble pruning is to find the best subset such that the combination of the selected classifiers will have the highest possible degree of accuracy. Consequently the problem can be formally phrased as follows: Ω ={ M1,..., Mn } , a combination method C, and a training set S Zopt ⊆ Ω . which minimizes the generalization error over the distribution D of the classification of classifiers in Zopt Note that we assume that the ensemble is given, thus we do not attempt to improve the creation of the original ensemble. It has been shown that the pruning effect is more noticeable on ensemble whose the diversity among its members is high (Margineantu and Dietterich, 1997). Boosting algorithms create diverse classifiers by using widely different parts of the training set at each iteration (Xxxxx et al., 2006). Specifically we employ the most popular methods for creating the ensemble: Bagging and AdaBoost. Bagging (Xxxxxxx, 1996) employs bootstrap sampling to generate several training sets and then trains a classifier from each generated training set. Note that, since sampling with replacement is used, some of the original instances may appear more than once in the same generated training set and some may not be included at all. The classifier predictions are often combined via majority voting. AdaBoost (Xxxxxx and Schapire, 1996) sequentially constructs a series of classifiers, where the training instances that are wrongly classified by a certain classifier will get a higher weight in the training of its subsequent classifier. The classifiers’ predictions are combined via weighted voting where the weights are determined by the algorithm itself based on the training error of each classifier. Specifically the weight of classifier i is determined by Equation 1: α = 1 ln ⎛ 1−εi ⎞
(1) ⎝ ⎠
