Incorrect Hypotheses Research Articles

Minimum Qof small Antennas

A detailed analysis is presented which shows that the method introduced by Collin and Rothschild in 1964 for finding the time averaged stored energy in the electromagnetic field surrounding a small antenna is valid and leads to correct evaluation of the minimum Q of a small antenna. An alternative method for finding the minimum Q of small antennas is also presented. This method is based on the natural complex resonant frequency of a TE or TM mode tuned to resonance by a reactive surface impedance on the minimum circumscribing sphere that encloses the antenna. This alternative method of finding the minimum Q of a small antenna is shown to give results in close agreement with the earlier results. The paper also provides a critique of recent work by D. M. Grimes and C. A. Grimes in which they claim that smaller antenna Q's can be obtained than that found by earlier investigators. It is shown that the results obtained by Grimes and Grimes are based on incorrect hypothesis and are wrong.

The effect of Gaussian error in object recognition

In model based recognition, the goal is to locate an instance of one or more known objects in an image. The problem is compounded in real images by the presence of clutter, occlusion, and sensor error, which can lead to false negatives, failures to recognize the presence of the object, and false positives, in which the algorithm incorrectly identifies an occurrence of the object. The probability of either event is affected by parameters within the recognition algorithm, which are almost always chosen in an ad-hoc fashion. The effect of the parameter values on the likelihood that the recognition algorithm will make a mistake are usually not understood explicitly. To address the problem, we explicitly model the noise that occurs in the image. In a typical recognition algorithm, hypotheses about the position of the object are tested against the evidence in the image, and an overall score is assigned to each hypothesis. We use a statistical model to determine what score a correct or incorrect hypothesis is likely to have, and use standard binary hypothesis testing techniques to distinguish correct from incorrect hypotheses. Using this approach, we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.

Method of optimizing a composite speech recognition expert

In a continuous speech recognizer which includes at least, one acoustic expert and one linguistic expert which generate respective scores, a method is disclosed for adjusting the relative weighting to be applied to those scores employing training data utilizing the words to be recognized in multiple word phrases. Multiple word test phrases are applied to the acoustic expert to determine, for each phrase, plural multi-word hypotheses each having corresponding cumulative scores. The linguistic expert generates corresponding cumulative linguistic scores. An objective function is calculated for each test phrase having a value which is variable as a function of the difference between the combined score of any correct hypothesis and that of the most easily confused incorrect hypothesis. The objective function values are cumulated and a gradient descent procedure is used to adjust the relative weighting of the acoustic and linguistic scores in obtaining a combined score.

An N-best candidates-based discriminative training for speech recognition applications

The authors propose an N-best candidates-based discriminative training procedure for constructing high-performance HMM speech recognizers. The algorithm has two distinct features: N-best hypotheses are used for training discriminative models; and a new frame-level loss function is minimized to improve the separation between the correct and incorrect hypotheses. The N-best candidates are decoded based on their recently proposed tree-trellis fast search algorithm. The new frame-level loss function, which is defined as a halfwave rectified log-likelihood difference between the correct and competing hypotheses, is minimized over all training tokens. The minimization is carried out by adjusting the HMM parameters along a gradient descent direction. Two speech recognition applications have been tested, including a speaker independent, small vocabulary (ten Mandarin Chinese digits), continuous speech recognition, and a speaker-trained, large vocabulary (5000 commonly used Chinese words), isolated word recognition. Significant performance improvement over the traditional maximum likelihood trained HMMs has been obtained. In the connected Chinese digit recognition experiment, the string error rate is reduced from 17.0 to 10.8% for unknown length decoding and from 8.2 to 5.2% for known length decoding. In the large vocabulary, isolated word recognition experiment, the recognition error rate is reduced from 7.2 to 3.8%. Additionally, they have found that using more relaxed decoding constraints in preparing N-best hypotheses yields better recognition results. >

Lines of thought: A ratio and operator model of rational number

A model of rational number is described that exploits the fact that a pair of line segments can embody a ratio of numbers and that actions upon segments can embody arithmetical operations. Tasks are described for bringing out diverse meanings of rational numbers. In the software under development algebraic equations are used for formulating descriptions of the relations among segments and for carrying out operations intended to display geometrically the meaning of the equations. Incorrect hypotheses produce arithmetic inequalities, represented in the model as resultant segments of unequal lengths; correct hypotheses produce resultant segments of equal lengths. None of the tasks discussed can be solved through rote numerical computation but require reflecting upon the relations of quantities. This aspect may be useful in drawing out the relational meaning of rational numbers.

Evaluating Negative Tests and Refutations in a Rule Discovery Task

Subjects participating in Wason's rule discovery task (1960) overwhelmingly try to confirm rather than refute their currently held hypothesis. Such a strategy is often inadequate and runs counter to the canons of scientific methodology. The present study was designed to investigate subjects’ differential evaluation of test strategies and outcome. One-hundred and sixty students participated in two experiments in which they had to judge someone else's potential test items in Wason's task. Experiment 1 demonstrated that exposure to various histories has a mediating effect on the strength of the confirmation bias. In Experiment 2, subjects knew the researcher's rule and thus whether each proposed test item would lead to confirmation or refutation of the hypothesis under consideration. The preferred items were those that alerted the subject to an incorrect hypothesis (refutation) and those that turned out to be positive instances of the rule sought after, with the combination of the two (a negative test leading to refutation) being most highly evaluated.

Confidence in evolutionary trees from biological sequence data.

The reliable construction of evolutionary trees from nucleotide sequences often depends on randomization tests such as the bootstrap and PTP (cladistic permutation tail probability) tests. The genomes of bacteria, viruses, animals and plants, however, vary widely in their nucleotide frequencies. Where genomes have independently acquired similar G+C base compositions, signals in the data arise that cause methods of evolutionary tree reconstruction to estimate the wrong tree by grouping together sequences with similar G+C content. Under these conditions randomization tests can lead to both the rejection of the correct evolutionary hypothesis and acceptance of an incorrect hypothesis (such as with the contradictory inferences from the photosynthetic rbcS and rbcL sequences). We have proposed one approach to testing for G+C content problem. Here we present a formalization of this method, a frequency-dependent significance test, which has general application.

Best probabilist estimates of non-linear system: structure determination

Abstracts The refinement method using the optimal algorithm has been formulated for crystal structure determination. This method includes, in the criterion, the a priori data consisting of probable interatomic distances by means of a repulsive-attractive term. The minimization mode used is a simplex mode. This method permits to make the refinement even from an incorrect structural hypothesis and also refuses to pass through physically unacceptable intermediate solutions.

GALILEO'S CONFIRMATION OF A FALSE HYPOTHESIS: A PARADIGM OF LOGICAL ERROR IN DESIGN

Abstract Galileo's classic analysis of a cantilever beam is explicated, and the contemporary persistence of the fundamental error he made in it is discussed. The incorrect hypothesis that Galileo set forth as his first proposition about the behavior of the beam is examined in the context of his pioneering analysis, as is the process whereby the erroneous basic assumption led to a result that was confirmed. The example of Galileo and the cantilever beam is presented as a paradigm for human error in engineering analysis and design, and it is argued that familiarity with such a paradigm among the community of engineering educators and practitioners can help reduce design erors and failures.

3D object recognition using invariant feature indexing of interpretation tables

This paper proposes a technique for 3D object recognition from range data. Our technique (which was motivated by recent work in geometric hashing) employs precompiled interpretation tables as a source of prototype hypotheses. These tables are indexed by invariant features computed from triples of surface patches. We describe a method for automated construction of interpretation tables from CAD models. Invariant features extracted from the input image are used to index the tables, retrieve prototype hypotheses, and bind them to scene entities. These candidate hypotheses are then ranked via computation of a matching score. The use of precompiled tables of hypotheses offers the potential for greater efficiency in the recognition step than techniques such as constrained search. Experiments demonstrate significant reductions in the number of incorrect hypotheses produced over a constrained search mechanism.

A higher-order linear theory for isotropic plates—I. Theoretical considerations

Using estimates of the strain field a new refined version of the linear theory of isotropic plates is constructed. The theory is expressed in terms of the same independent parameters of displacements as in the first-order shear deformation theory. The accuracy of the strain energy in this theory is of the order (h/L)4 (h-thickness, L-wavelength of deformation patterns) whereas the classical theory of plates has accuracy of the order h/L)2. The results of the present analysis provide evidence that some of the earlier proposed higher-order theories of isotropic plates are based on an incorrect hypothesis for the displacement field.

An intraweek seasonality in the implied volatilities of T-bond and T-note options

This paper initiates the study of intraweek seasonalities in the implied volatilities of options on futures contracts on U.S. Treasury bonds and notes. Research on intraweek regularities is important to public policy because the structure and usage of derivative markets is a regulatory issue. The topic is also important to discussions of market efficiency. For example, empirical observation of various trading regularities has stimulated research into market closing effects, weekend perturbations in discount rates, and patterns in news dissemination. Other theoretical topics which are stimulated by day-of-the-week research are models of bid-asked spreads (Roll [21]), trading concentration due to the interaction of liquidity and information traders (Admati and Pfleiderer [l]), and the role of noise and its effect on liquidity (Black [4]). Poole [20] and Eisemann and Timme [4] discuss the micro-mechanics of the Federal Reserve system and the Federal funds market. Stigum [23] and Melton [16] provide anecdotal evidence of high Friday and Wednesday volatility of the Federal funds rate. Dyl [7] concludes that Friday Federal funds rates are on average higher than other days. Spindt and Hoffmeister [22] explain how the mechanics of the Federal funds system lead to high variability of rates on Friday, especially on the second Friday of each reporting period. Findings of intraweek regularities have often been accompanied by analysis of particular institutional features or related anomalies (see, for example, PhillipsPatrick and Schneeweis [19] who relate high Monday dividends to the putative Monday effect in stocks, or Jaffe and Westerfield [12] who study the effects of currency seasonals and clearing procedures in the weekend effect context). A healthy skepticism should prevail in all discussions of intraweek regularities. Using a Bayesian approach, Connally [S] claims that most perceived anomalies of this type are due to incorrect hypothesis testing procedures, unduly large samples and historical accidents.

Learning from experience: differences in how novice vs. expert nurses diagnose why an infant is crying.

Diagnosing client health problems is a well-recognized task for nurses. This study examined the effects of nursing education and experience on that problem-solving process by comparing the performance of four groups of nurses. Junior and senior nursing students, nursing students who were parents, and pediatric nurses solved two computer-presented problems. The task involved acquiring information in order to evaluate competing causal hypotheses. One problem concerned why an infant was crying and the other was a control problem. A number of group differences were identified. The experienced groups of pediatric nurses and parents differed from the student nurses by using less information and selecting different information units, such as information about the infant's age, earlier in the problems. Parents were the most accurate; they did not select any incorrect hypotheses. The dual roles of education and experience are discussed and it is proposed that computer-presented simulations can be an important tool for understanding problem-solving processes, as well as for promoting clinical skill development.

Reward Context: Influence on Hypotheses during Learning Set Formation by Preschool Children

Previous studies have shown that, compared to separate reward, a reward sticker attached to the underside of the positive stimulus facilitates solution of discrimination problems by preschool children. It is established here that the context of reward also affects the formation of learning set over a series of discrimination problems and that the improvement is characterized by a reduced frequency (from 19% to 7%) of incorrect position-related hypotheses (error factors) and an increased frequency (from 34% to 65%) of object-related hypotheses.

Computer assisted diagnosis and computer consultation in neurology: preliminary testing of diagnostic accuracy for the neurologist system.

The Neurologist system is a computer program for consultation in clinical neurology which employs human-like reasoning in diagnosis, covers a broad diagnostic domain, has the capacity to explain strategies and conclusions and is readily expandable. Neurologist employs the strategy of first localizing a neurologic disease, then uses these data as well as mode of disease onset, rapidly to focus on a limited number of diagnostic possibilities which are then sequentially investigated. This paper presents the results of the preliminary assessment of Neurologist's diagnostic accuracy. For a set of 30 test cases, the system's leading diagnosis was correct in 77%, and separation of correct and incorrect diagnostic hypotheses was excellent. Further evaluations of the system are in progress.

Aspects of a theory of language acquisition.

ABSTRACTThis paper presents a hypothesis-testing theory of syntax acquisition. The first section presents our model. We claim that: (1) children learn a transformational grammar, including a set of phrase structure and transformational rules; (2) linguistic universals and Occam's razor constrain the initial hypothesis space available to the device; (3) hypotheses tested by the device consist of candidate phrase structure and transformational rules; (4) linguistic evidence confirms or disconfirms hypotheses. Specific examples of incorrect phrase structure and transformational hypotheses are presented.The second section briefly surveys other approaches to language acquisition – both syntactic and non-syntactic – and compares them to our model. In the third section, we address several methodological issues: (1) the relevance of linguistic theory to the model; (2) how the model is tested; (3) the domain of the theory.

Chernoff bounds for discriminating between two markov processes

We study a statistical hypothesis testing problem, where a sample function of a Markov process with one of two sets of known parameters is observed over a finite time interval. When a log likelihood ratio test is used to discriminate between the two sets of parameters, we give bounds on the probability of choosing an incorrect hypothesis, and on the total probability of error, for both discrete and continuous time parameter, and discrete and continuous state space. The asymptotic behavior of the bounds is examined as the observation interval becomes infinite.

Impaired performance by adult humans: Learned helplessness or wrong hypotheses?

Seligman and his associates demonstrated that following a series of uncontrollable, stressful events dogs fail to respond on simple tasks. Seligman accounted for this with a learned-helplessness hypothesis, that uncontrollable events produce a subject who perceives that response is useless and whose motivation to respond is weakened. Recently, analogous experiments have been performed with adult human subjects. Impairment of problem solving has been demonstrated following failure on a prior task. The same learned-helplessness hypothesis has been invoked for this result. The present thesis is that these human experiments may be equally well interpreted by Hypothesis Theory. According to Hypothesis Theory, failure produces subsequent impairment in performance not because subjects are helpless but because they are misdirected about the nature of the solution. That is, these subjects are not passive. Rather, they test incorrect hypotheses. Experimental data are presented to suggest the validity of the Hypothesis Theory interpretation.

Confirmation Bias in a Simulated Research Environment: An Experimental Study of Scientific Inference

Numerous authors (e.g., Popper, 1959) argue that scientists should try to falsify rather than confirm theories. However, recent empirical work (Wason and Johnson-Laird, 1972) suggests the existence of a confirmation bias, at least on abstract problems. Using a more realistic, computer controlled environment modeled after a real research setting, subjects in this study first formulated hypotheses about the laws governing events occurring in the environment. They then chose between pairs of environments in which they could: (I) make observations which would probably confirm these hypotheses, or (2) test alternative hypotheses. Strong evidence for a confirmation bias involving failure to choose environments allowing tests of alternative hypotheses was found. However, when subjects did obtain explicit falsifying information, they used this information to reject incorrect hypotheses.

Retroactive interference in single‐cue probability learning

Abstract.— When two single‐cue probability learning tasks with different amounts of unpredictable variance were learned in succession. a low variance task interfered with the retention of a high variance task, but the opposite was not true. The effects were positive in that they enabled the subjects to reach a higher response consistency and, thus, a higher level of achievement. It was suggested that the subjects made use of the low variance task to reject incorrect hypotheses about the cue‐criterion relation and that interference from an interpolated task occurs only when this task provides information which has functional value for the subject.