Matching

This article surveys deformable models, a promising and vigorously researched computer-assisted medical image analysis technique. Among model-based techniques, deformable models offer a unique and powerful approach to image analysis that combines geometry, physics, and approximation theory. They have proven to be effective in segmenting, matching, and tracking anatomic structures by exploiting (bottom-up) constraints derived from the image data together with (top-down) a priori knowledge about ...

The low noise amplifier is one of the basic functional blocks in communication systems. The main interest of the LNA at the input of the analog processing chain is to amplify the signal without adding significant noise. In this work, we have modeled a LNA for radar reception systems operating around 11 GHz, using the technique of impedance transformations with Smith chart utility. The type of transistor used is: the transistor HEMT AFP02N2-00 of Alpha Industries®. The results show that the modeled amplifier has a gain greater than 20 dB, a noise figure less than 2 dB, input and output reflection coefficients lower than-20 dB and unconditional stability. Keyword: Gain Low noise amplifier (LNA) Matching Noise figure Stability

This paper presents a novel electronically tunable slot antenna. The design is based on a resonant slot structure loaded with a series of PIN diode switches. The tuning of the operating frequency is realized by varying the electrical length of the antenna, which is controlled by the DC bias voltages of the switches. The fabricated antenna is capable of resonating at four different frequencies ranging from 550 to 900 MHz. Very good matching is achieved for all resonant frequencies without the need for any special matching network. Additionally, it is demonstrated that the radiation pattern, efficiency and polarization remain essentially unaffected by the frequency tuning.

Entrepreneurs and investors face challenges in the 'thin market' for early stage entrepreneurial finance. Improving this situation has been a priority of policy makers for at least a decade, however, the challenges in this matching process are still poorly understood. Theory suggests that matching problems may originate in different perceptions in areas such as evaluation criteria, risk and risk management by investors and entrepreneurs. To find a good match it seems essential to understand what is important to your counterpart. Based on a mixed methods approach using data collected in semi-structured interviews and a survey with both entrepreneurs and investors mostly active in green tech innovation, this study systematically analyses where their perceptions deviate and where frictions in the matching process may occur. We find that a mismatch exists in the perception of risk, the importance attached to risk, the search channels used to find a potential partner and the evaluation criteria applied in evaluating a proposition (i.e., exit, innovativeness, capabilities of teams). This paper suggests that increasing market transparency and creating a mutual understanding of the investment process will prevent potentially damaging perception misalignment from arising in the first place.

Performance limitations on current-steering digital-to-analog converters (DACs) are due to finite output impedances, nonideal switches, parasitic capacitances, matching, etc. In this work we present a dynamic state-space model of a 14-bit current-steering DAC which includes dynamic nonidealities. Simulation results are presented and compared to measurement results. The model can be used for fast performance estimation of D/A converters

Over the past several years, researchers within the ONR-sponsored Adaptive Architectures for Command and Control (A2C2) research program have been investigating the concept of organizational "congruence." These model-based theories loosely state that the better an organization is matched structurally to the overall mission (as measured using a multi-variant set of workload/congruence metrics) the better will that organization perform, and that mismatches are potential drivers for the adaptation of organization structure. To test the congruence theories and their corollaries in a laboratory experiment, the authors' approach was to seek two sufficiently disparate organizational structures and then design two missions (or scenarios) that would exploit the differences in these two structures. One scenario would be "tuned" to organization 1 to exhibit a high degree of congruence, but at the same time it would be "mismatched" (i.e., exhibit low congruence...

The Stable Matching problem was introduced by Gale and Shapley in 1962. The input for the stable matching problem is a complete bipartite K n,n graph together with a ranking for each node. Its output is a matching that does not contain a blocking pair, where a blocking pair is a pair of elements that are not matched together but rank each other higher than they rank their current mates. In this work we study the Distributed Weighted Stable Matching problem. The input to the Weighted Stable Matching problem is a complete bipartite K n,n graph and a weight function W. The ranking of each node is determined by W, i.e. node v prefers node u 1 over node u 2 if W((v,u 1)) > W((v, u 2)). Using this ranking we can solve the original Stable Matching problem. We consider two different communication models: the billboard model and the full distributed model. In the billboard model, we assume that there is a public billboard and each participant can write one message on it in each time step. In the distributed model, we assume that each node can send O(logn) bits on each edge of the K n,n . In the billboard model we prove a somewhat surprising tight bound: any algorithm that solves the Stable Matching problem requires at least n − 1 rounds. We provide an algorithm that meets this bound. In the distributed communication model we provide an algorithm named intermediation agencies algorithm, in short (IAA), that solves the Distributed Weighted Stable Marriage problem in $O(\sqrt{n})$ rounds. This is the first sub-linear distributed algorithm that solves some subcase of the general Stable Marriage problem.

We introduce a novel fingerprint representation scheme that relies on describing the orientation field of the fingerprint pattern with respect to each minutia detail. This representation allows the derivation of a similarity function between minutiae that is used to identify corresponding features and evaluate the resemblance between two fingerprint impressions. A fingerprint matching algorithm, based on the proposed representation, is developed and tested with a series of experiments conducted on two public domain collections of fingerprint images. The results reveal that our method can achieve good performance on these data collections and that it outperforms other alternative approaches implemented for comparison.

ISO has recently published Part 7 of the ISO/IEC 15504 standard, with the aim of determining the extent to which an organization consistently implements processes that contribute to achievement of its business goals. This new Part 7 of ISO/IEC 15504 has addressed issues related to the assessment of organizational maturity, as the CMMI-DEV model also does. Recently, growing interest has been shown towards the need to harmonize different improvement models or standards, thereby presenting an integrated vision about them. All this being so and in an effort to offer information on how the maturity levels described in these two models are related, we have carried out the harmonization of these two models. It is based, firstly, on a mapping between processes of ISO 12207:08 and process areas of CMMI-DEV, and in second place, on a matching between processes of ISO 12207:08 and ISO 15504-5. For this work, we have taken into account the latest versions of the models, and defined a suitable process to carry out the mapping in a systematic way. We established differences and similarities between the maturity levels (and their processes) described in these models, our goal being to support organizations which are interested in tackling organizational maturity. Copyright © 2009 John Wiley & Sons, Ltd.

In this paper, a neural network based optimization method is described in order to solve the problem of stereo matching for a set of primitives extracted from a stereoscopic pair of images. The neural network used is the 2D Hopfield network. The matching problem amounts to the minimization of an energy function involving specified stereoscopic constraints. This function reaches its minimum when these constraints are satisfied. The network converges to its stable state when the minimum is reached. In the initial step, the primitives to match are extracted from the stereoscopic pair of images. The primitives we use are specific points of interest. The feature extraction technique is the one developed by Moravec, and called the interest operator. Its output comprises mostly corners or feature points with high variance. The Hopfield network is represented as a N l × N r matrix of neurons, where N l is the number of features in the left image and N r the number of features in the right one. An update of the state of each neuron is done in order to perform the network evolution and then allowing it to settle down into a stable state. In the stable state, each neuron represents a possible match between a left candidate and a right one.