다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

The Theory of Matrices. By F R. Gantmacher. Two volumes, pp. 374 and 276. 1959. (Translated from the Russian by K. A. Hirsch; Chelsea Publishing Company, New York)

Antenna Theory And Design

In general, Micropower Impulse Radar (MIR) depends on Ultra-Wideband (UWB) transmission systems. UWB technology can supply innovative new systems and products that have an obvious value for radar and communications uses. Important applications include bridge-deck inspection systems, ground penetrating radar, mine detection, and precise distance resolution for such things as liquid level measurement. Most of these UWB inspection and measurement methods have some unique qualities, which need to be pursued. Therefore, in considering changes to Part 15 the FCC needs to take into account the unique features of UWB technology. MIR is applicable to two general types of UWB systems: radar systems and communications systems. Currently LLNL and its licensees are focusing on radar or radar type systems. LLNL is evaluating MIR for specialized communication systems. MIR is a relatively low power technology. Therefore, MIR systems seem to have a low potential for causing harmful interference to other users of the spectrum since the transmitted signal is spread over a wide bandwidth, which results in a relatively low spectral power density.

/pdf/response-to-fcc-98-208-notice-of-inquiry-in-the-matter-of-3attixctl7.pdf

Response to FCC 98-208 notice of inquiry in the matter of revision of part 15 of the commission's rules regarding ultra-wideband transmission systems

There is a wide number of problems in electromagnetic (EM) engineering that require a real-time response or in which the input–output relationship is not a-priori known or cannot be defined due to ...

Learning-by-examples techniques as applied to electromagnetics

In this paper, an innovative strategy for the passive localization of transceiver-free objects is presented. The localization is yielded by processing the received signal strength data measured in an infrastructured environment. The problem is reformulated in terms of an inverse source one, where the probability map of the presence of an equivalent source modeling the moving target is looked for. Toward this end, a customized classification procedure based on a support vector machine is exploited. Selected, but representative, experimental results are reported to assess the feasibility of the proposed approach and to show the potentialities and applicability of this passive and unsupervised technique. “(c) Institute of Physics”

/pdf/electromagnetic-passive-localization-and-tracking-of-moving-20rmp7n31j.pdf

Electromagnetic passive localization and tracking of moving targets in a WSN-infrastructured environment

An analytical method based on Interval Analysis (IA) is proposed to predict the impact of the manufacturing tolerances of the excitation amplitudes on the radiated array pattern. By expressing the array factor according to the rules of the Interval Arithmetic, the radiation features of the linear array are described in terms of intervals whose bounds are analytically determined as functions of the nominal value and the tolerances of the array amplitudes. A set of representative numerical experiments dealing with different radiated beams and linear array sizes is reported and discussed to point out the features and potentials of the proposed approach.

Tolerance Analysis of Antenna Arrays Through Interval Arithmetic

In this paper, the synthesis of subarrayed antennas with subarrays having different weights and dimensions is considered. The problem is formulated as the definition of the element clustering into spatially contiguous subarrays and the corresponding weights to obtain a pattern with the lowest (i.e., minimum achievable) sidelobe level (SLL). The problem is addressed with an unconstrained approach based on an excitation matching method where the synthesis of subarray weights and sizes is simultaneously carried out. Successively, a hybrid version of such an approach is proposed to directly enforce into the optimization procedure the SLL constraints. A set of representative results concerned with both sum and difference patterns are shown. Furthermore, some comparisons with state-of-the-art hybrid evolutionary-based techniques are reported, as well.

Design of Subarrayed Linear and Planar Array Antennas With SLL Control Based on an Excitation Matching Approach

The design of phased arrays generating low sidelobes and grating-lobes-free patterns over wide frequency bandwidths is addressed. The array structure is decomposed in subarrays with irregular polyomino tiles whose locations and orientations are optimized by means of a genetic algorithms-based approach. A set of representative results is reported and discussed to give some insights on the performance of the proposed approach also in comparison to state-of-the-art solutions.

Paolo Rocca

Papers

Learning-by-examples techniques as applied to electromagnetics

Electromagnetic passive localization and tracking of moving targets in a WSN-infrastructured environment

Tolerance Analysis of Antenna Arrays Through Interval Arithmetic

Design of Subarrayed Linear and Planar Array Antennas With SLL Control Based on an Excitation Matching Approach

GA-Based Optimization of Irregular Subarray Layouts for Wideband Phased Arrays Design