1,720,978 research outputs found
Garzustandsvorhersage mittels Sensordatenfusion von Klima- und Hochfrequenzsensoren in einem Gargerät
No full textAutomating cooking processes in professional cooking appliances requires the knowledge of the food's state in the cooking chamber - especially its changes over time. The core temperature or the size of the food to be cooked are of interest, as these are key factors in determining the required cooking climate and the cooking time. In a combinational oven with circulating hot air and passive solid state microwave sources, the actuator and sensor tracks contain indirect information about the food being cooked. The actuators define the cooking climate and the S-parameters of the passive microwave sources serve as sensors. In this work, the inverse problem of probabilistic state estimation is formulated as a sensor data fusion. Based on the S-parameters, a feature is introduced to approximate the quality factor of the microwave cavity. In this context, the approximate quality factor represents a crucial source of information about the actual state since it is correlated with the absorbed power of the food item. To simulate the cooking of chicken breast meat, a system of heat and mass transfer equations coupled with Maxwell's equations can be used. This creates a dataset of varying cooking processes to study sensor data fusion. In cooking applications, the Markov property is generally not fulfilled since the previous cooking climate significantly influences the state changes. To account for long-term dependencies, Long Short-Term Memory networks are used to model the state changes. Extending the network with a second neural network, and training the combined network architecture with a maximum likelihood estimation approach, allows accounting the underlying uncertainty. Thus, a direct probabilistic state estimation of the core temperature based on the cooking climate and approximate quality factor is realized. To implement a recursive state estimation using a Bayes filter, the microwave volume model is introduced to model the likelihood function. Based on the cooking geometry and the temperature dependent permittivity, the absorbed power of the food item can be estimated. The latter is correlated with the approximate quality factor. Following the direct state estimation the state transition function is modeled. The probabilistic core temperature prediction is evaluated on an experimental data set only using simulation data to train the networks
Resource allocation for future wireless relay systems
No full textIn future wireless communication systems, full-duplex (FD) and massive multiple-input-multiple-output (mMIMO) are considered as two promising technologies to overcome capacity crunch and spectrum scarcity. Transmission and reception at the same frequency-time channel in FD and large antenna arrays in mMIMO systems improve the spectral efficiency to a great extent compared to current systems. To make mMIMO systems cost-efficient, inexpensive less-accurate transmit and receive chain components are preferred. This leads to hardware distortions, which in turn becomes unfavourable for self-interference (SI) cancellation in FD systems. In this thesis, our main goal is to design distortion-aware FD multi-antenna multi-carrier (MC) systems, from the aspect of resource allocation and the resulting system performance. Particularly the impact of distortions caused by hardware impairments, leading to residual self-interference and inter-carrier leakage as well as the imperfect channel state information is taken into account. Initially, we investigate the linear transceiver design problem for an FD multiple-input-multiple-output (MIMO) MC decode and forward (DF) relaying system. In addition to the traditional per-carrier DF relaying, the case with a joint-carrier DF is also studied, taking advantage of group-wise decoding and encoding. An alternating quadratic convex program is proposed for the resulting non-convex optimization problem, where a monotonic improvement at each iteration leads to a guaranteed convergence. Furthermore, we focus on the joint sub-carrier and power allocation problem for a DF relay system, where multiple half-duplex (HD) single antenna (SA) MC source-destination pairs communicate with the aid of an FD mMIMO MC relay. Apart from focusing on maximizing the sum-rate and energy efficiency, we also focus on minimizing the overall delivery time for a given set of communication tasks to the user nodes. Due to the intractable nature of the allocation problem, an iterative solution is proposed, employing the successive inner approximation framework, with guaranteed convergence to a point that satisfies the Karush-Kuhn-Tucker optimality conditions. This approach is then extended to a bi-directional communication system, where an FD mMIMO MC base station (BS) serves multiple FD SA MC nodes. Finally, we focus on the problem of resource allocation for an FD-enabled relaying system, where an mMIMO MC BS simultaneously activates the relay as well as the direct channel for communicating separate data streams to the user terminals. This is implemented by employing successive interference cancellation (SuIC) at the MC SA user terminals. Besides the superior performance under various system conditions, the proposed dual-connectivity enjoys higher robustness when one of the active paths experience an unexpected blockage. Numerical results show the significance of distortion-aware design for FD mMIMO MC systems, particularly in the presence of a strong SI channel or low-resolution hardware. Moreover, a notable gain is observed compared to its HD counterparts when SI is efficiently suppressed. In the case of dual-connectivity scenario, numerical results show the performance gain of our proposed SuIC scheme in terms of sum-rate compared to single-connectivity and HD schemes
On the efficient signal processing and positioning schemes for wireless sensor networks
No full textA wireless sensor network (WSN) consists of many densely deployed sensor nodes that are often randomly distributed in an area. The sensor nodes are small in size with low computational capacity and limited power. The goal of a WSN is to collect data about a phenomenon by a group of sensor nodes and forward them to a sink node or a fusion center for further processing. In this thesis, three major topics are investigated regarding efficient signal processing and positioning schemes in WSNs. First, a set-membership affine projection algorithm is proposed that can estimate a complex-valued channel matrix using a set of complex-valued pilots in the presence of the additive white Gaussian noise. The algorithm is thoroughly investigated, the convergence is proved and the error performance is analytically studied. It is also shown that the algorithm converges faster than the well-known set-membership normalized least mean square algorithm (SM-NLMS) while it resolves the high steady-state error value and the complexity issues in the regular affine projection algorithm. In the second part, we consider a target detection scenario, where a fast multi-target detection technique—using a devised precoding for WSNs—is proposed. The targets in the WSN are detected by binary wireless sensors which only have one or zero logical outputs, indicating the presence or absence of targets, respectively. The goal is to simultaneously decode the data of all sensors within one time slot at the receiver, where all independent sensors transmit data at the same time and operate on the same frequency band. The precoding is devised such that the detection error is minimized at the receiver. Finally, the receiver positioning problem is investigated, where the transmitters are distributed arbitrarily on the XY-plane with known positions. The goal is to find the optimal solution for the position of the receiver such that the maximum distance between the receiver and the transmitters is minimized, while two constraints are fulfilled as follows: for any pair of transmitters, the delay caused by the difference in the distances between the transmitters and the receiver is less than a certain value, and the angle between the line-of-sight paths from each transmitter toward the receiver is within a tolerable range
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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