High Information Gain Research Articles

Adaptive Observation Strategy for Dispersion Process Estimation Using Cooperating Mobile Sensors

Efficient online state estimation of dynamic dispersion processes plays an important role in a variety of safety-critical applications. The use of mobile sensor platforms is increasingly considered in this context, but implies the generation of situation-dependent vehicle trajectories providing high information gain in real-time.In this paper, a new adaptive observation strategy is presented combining state estimation based on partial differential equation models of the dispersion process with a model-predictive control approach for multiple cooperating mobile sensors. In a repeating sequential procedure, based on the Ensemble Transform Kalman Filter, the uncertainty of the current estimate is determined and used to find valuable measurement locations. Those serve as target points for the controller providing optimal trajectories subject to the vehicles' motion dynamics and cooperation constraints. First promising results regarding accuracy and efficiency were obtained.

Alarm allocation for event-based process alarm systems

The ability to monitor large numbers of variables and the flexibility to assign alarms to each variable led to a substantial increase in the numbers of alarms in industrial plants. This, in turn, increased the numbers of false and redundant alarms. In plant operations, the numbers of annunciated alarms regularly exceed the acceptable rates that operators can handle. To reduce the number of assigned alarms, a risk-based alarm system has been proposed in the literature (Ahmed et al. (2011); Chang et al. (2011)) where alarms are assigned to groups of variables instead of individual variables. This articles explores the options for grouping variables for alarm allocation. Several grouping methods are discussed and an event-based grouping procedure is detailed. Selection of the key variables for a group is performed using the information that the variables can have to distinguish between an abnormal and a normal condition. The concept of mutual information is used to quantify the information. Variables with high information gain are grouped together for each respective abnormal event. To identify the redundant variables within the groups to further reduce the number of variables to be monitored, the maximum cross-correlation between pairs of key variables are used. A case study using the example of a continuous stirred tank reactor is used to demonstrate the methodology.

Active learning of expressive linkage rules using genetic programming

A central problem in the context of the Web of Linked Data as well as in data integration in general is to identify entities in different data sources that describe the same real-world object. Many existing methods for matching entities rely on explicit linkage rules, which specify the conditions which must hold true for two entities in order to be interlinked. As writing good linkage rules by hand is a non-trivial problem, the burden to generate links between data sources is still high. In order to reduce the effort and expertise required to write linkage rules, we present the ActiveGenLink algorithm which combines genetic programming and active learning to generate expressive linkage rules interactively. The ActiveGenLink algorithm automates the generation of linkage rules and only requires the user to confirm or decline a number of link candidates. ActiveGenLink uses a query strategy which minimizes user involvement by selecting link candidates which yield a high information gain. Our evaluation shows that ActiveGenLink is capable of generating high quality linkage rules based on labeling a small number of candidate links and that our query strategy for selecting the link candidates outperforms the query-by-vote-entropy baseline.

Active Learning of Expressive Linkage Rules Using Genetic Programming

A central problem in the context of the Web of Linked Data as well as in data integration in general is to identify entities in different data sources that describe the same real-world object. Many existing methods for matching entities rely on explicit linkage rules, which specify the conditions which must hold true for two entities in order to be interlinked. As writing good linkage rules by hand is a non-trivial problem, the burden to generate links between data sources is still high. In order to reduce the effort and expertise required to write linkage rules, we present the ActiveGenLink algorithm which combines genetic programming and active learning to generate expressive linkage rules interactively. The ActiveGenLink algorithm automates the generation of linkage rules and only requires the user to confirm or decline a number of link candidates. ActiveGenLink uses a query strategy which minimizes user involvement by selecting link candidates which yield a high information gain. Our evaluation shows that ActiveGenLink is capable of generating high quality linkage rules based on labeling a small number of candidate links and that our query strategy for selecting the link candidates outperforms the query-by-vote-entropy baseline.

Linear Precoding for Relay Networks: A Perspective on Finite-Alphabet Inputs

This paper considers the precoder design for dual-hop amplify-and-forward relay networks and formulates the design from the standpoint of finite-alphabet inputs. In particular, the mutual information is employed as the utility function, which, however, results in a nonlinear and nonconcave problem. This paper exploits the structure of the optimal precoder that maximizes the mutual information and develops a two-step algorithm based on convex optimization and optimization on the Stiefel manifold. By doing so, the proposed algorithm is insensitive to initial point selection and able to achieve a near global optimal precoder solution. Besides, it converges fast and offers high mutual information gain. These advantages are verified by numerical examples, which also show the large performance gain in mutual information also represents the large gain in the coded bit-error rate.

Estimation of thermodynamic parameters of the biosphere, based on remote sensing

A method that allows the estimation of the thermodynamic parameters of the biosphere has been developed. It results in the subdivision of the following four phase states of the biosphere: three equilibrium states: “white planet” with high albedo and low entropy; temperate forest in winter with high entropy; and desert with high entropy; and one nonequilibrium state: the “active forests” with low entropy, high information gain and the highest exergy values. The phase shift to a nonequilibrium state happens when albedo is less than 0.2.

Co-evolution positions and rules for antigenic variants of human influenza A/H3N2 viruses

BackgroundIn pandemic and epidemic forms, avian and human influenza viruses often cause significant damage to human society and economics. Gradually accumulated mutations on hemagglutinin (HA) cause immunologically distinct circulating strains, which lead to the antigenic drift (named as antigenic variants). The "antigenic variants" often requires a new vaccine to be formulated before each annual epidemic. Mapping the genetic evolution to the antigenic drift of influenza viruses is an emergent issue to public health and vaccine developmentResultsWe developed a method for identifying antigenic critical amino acid positions, rules, and co-mutated positions for antigenic variants. The information gain (IG) and the entropy are used to measure the score of an amino acid position on hemagglutinin (HA) for discriminating between antigenic variants and similar viruses. A position with high IG and entropy implied that this position is highly correlated to an antigenic drift. Nineteen positions with high IG and high genetic diversity are identified as antigenic critical positions on the HA proteins. Most of these antigenic critical positions are located on five epitopes or on the surface based on the HA structure. Based on IG values and entropies of these 19 positions on the HA, the decision tree was applied to create a rule-based model and to identify rules for predicting antigenic variants of a given two HA sequences which are often a vaccine strain and a circulating strain. The predicting accuracies of this model on two sets, which consist of a training set (181 hemagglutination inhibition (HI) assays) and an independent test set (31,878 HI assays), are 91.2% and 96.2% respectively.ConclusionOur method is able to identify critical positions, rules, and co-mutated positions on HA for predicting the antigenic variants. The information gains and the entropies of HA positions provide insight to the antigenic drift and co-evolution positions for influenza seasons. We believe that our method is robust and is potential useful for studying influenza virus evolution and vaccine development.

고성능 AIPS 내의 연산증폭기에 대하여 부저항소자를 사용한 이득개선방법

고성능 VLSI 아날로그 정보처리시스템(AIPS)에서 고 이득 Op-Amp는 기본적 정보처리소자이다. 증폭기는 시스템 내 피드백루프에 사용시 안정도와 정확도를 얻기 위하여 고 이득이 요구된다. 1단의 증폭으로 이득이 충분하지 않을 경우 이득 부스팅 또는 추가적인 이득단이 필요하다. 본 논문에서 부 저항소자를 사용할 경우 이득이 개선되며 1단으로 고 이득을 손쉽게 얻을 수 있음을 보였다. 기존의 방법에 비교하여 본 연구에 제안된 방법은 전 출력 스윙, 적은 회로면적과 전력소비, 그리고 여러 구조의 증폭기에 적용가능 하다는 잇점을 지니고 있다. 부 저항소자는 Op-Amp에 사용될 경우 (+)와 (-) 차동출력 사이에 설치되어 증폭기 출력저항을 상쇄한다. 부 저항소자를 교차 연결된 CMOS 인버터의 형태로 구현할 경우 간단한 구조로서 40 dB 보다 더 큰 이득개선을 손쉽게 얻을 수 있음을 HSPICE 시뮬레이션을 통하여 확인하였다. In the high performance Analog Information Processing Systems(AIPS), gain boosting or additional gain stage is required when the gain is not sufficient with one stage amplification. This work shows that high gain is neatly obtained by enhancing the gain using the negative resistance element. Compared to the conventional techniques, the proposed scheme enjoys full output swing, small circuit area and power consumption, and the applications to various configurations of amplifiers. The negative resistance element is placed between the differential output nodes when used in the Op-Amp. The HSPICE simulation indicates that enhancement of more than 40 dB is readily obtained in this simple configuration when the negative resistance element is implemented in the form of cross-coupled CMOS inverters.

Application of reference materials for quality assessment in neutron activation analysis-use of information theory

It is generally accepted that an analytical procedure can be regarded as an information production system yielding information on the composition of the analyzed sample. Thus, information theory can be useful and the quantities characterizing the information properties of an analytical method may be applied not only as evaluation criteria but also as objective functions in the optimization. The usability of information theory is demonstrated on the example of neutron activation analysis. Both precision and bias of NAA results are taken into account together with the possible use of reference materials for quality assessment. The influence of the above-mentioned parameters on information properties such as information gain and profitability of NAA results is discussed in detail. It has been proved that information theory is especially useful in choosing suitable reference materials for the quality assessment of routine analytical procedures not only with respect to matrix and analyte concentration in the sample but also to concentrations and uncertainties of certified values in the CRM used. In the extreme trace analysis, CRMs with relatively large uncertainties and very low certified concentrations can still yield rather high information gain of results.

How to achieve a high information gain of results of quantitative analyses

The effect of procedure optimization, good laboratory practice and quality data control on the information gain of quantitative analyses and on its time stability is discussed.

The Observation of Monochromatic Intensity Distributions in Planetary Nebulae by Means of Electronography

The linear response and high information gain of the electronographic process make it an important new technique for the observation of monochromatic intensity distributions in planetary nebulae. Preliminary results for NGC 6720, obtained with the U.S. Navy electronic camera and the 61-inch astrometric reflector, are presented.