Test Strings Research Articles

Instance theory predicts categorization decisions in the absence of categorical structure: A computational analysis of artificial grammar learning without a grammar.

Theories of categorization have historically focused on the stimulus characteristics to which people are sensitive. Artificial grammar learning (AGL) provides a clear example of this phenomenon, with theorists debating between knowledge of rules, fragments, whole strings, and so on as the basis of categorization decisions (i.e., stimulus-driven explanations). We argue that this focus loses sight of the more important question of how participants make categorization decisions on a mechanistic level (i.e., process-driven explanations). To address the problem, we derived predictions from an instance-based model of human memory in a pseudo-AGL task in which all study and test strings were generated randomly, a task that stimulus-driven explanations of AGL would have difficulty accommodating. We conducted a standard AGL experiment with human participants using the same strings. The model's predictions corresponded to participants' decisions well, even in the absence of any experimenter-generated structure and regardless of whether test stimuli contained any incidental structure. We argue that theories of categorization ought to continue shifting towards the goal of modeling categorization at the level of cognitive processes rather than primarily attempting to identify the stimulus characteristics to which participants are drawn.

Dynamic response of deepwater test string under fluctuations in axial force and internal pressure

In this study, a mechanical model suitable for deepwater test string was proposed. An analysis of the dynamic response of the test string under different frequencies, different water depths and different fluctuation amplitudes was carried out by using the finite element method based on the change in the internal pressure and axial force measured. The results of the analysis showed that the response parameters (maximum stress and maximum deformation) tended to be stable after one period of fluctuation in the axial force and half a period of fluctuation in the internal pressure, respectively. When a sine waveform fluctuation in the internal pressure and axial force occurred, the response parameters increased with an increase in the amplitude of the fluctuation and increased with an increase in the frequency of fluctuation, and the amplitude of variation decreased with an increase in the fluctuation period. Under fluctuation in the axial force, the response parameter decreased with an increase in the water depth. The response parameter decreased first and then increased with an increase in the water depth when the fluctuation in the internal pressure occurred with a sine waveform. The maximum deformation and stress of the test string always changed with a change in the load when the fluctuation in the internal pressure and axial force had a sine waveform, and the test string under a load with a sine waveform was prone to periodic fatigue failure. The relevant conclusions provide a basis for the analysis and prevention of fatigue failure in test strings.

Mismatch losses in a PV system due to shortened strings

Numerous events may require intentional removal of one or more photovoltaic modules from a string, shortening the length of the string relative to others within the array, resulting in a str ing length mismatch. The impact of such a mismatch is not well understood either in measurable operational effects (voltage, current, power) or in the potential effects on long-term module health. It is impractical to solely approach this problem experimentally due to the size and complexity of arrays that may experience string length shortening. This work presents simulations, validated through limited field experiments on a two string array, providing a basis from which more complex arrays and scenarios may be explored. Refinement of the simulation achieves an overall error in IMPP for the nominal (S1) and test strings (S2) between the simulation and experimental values, through all test conditions, of +0.35±1.46% and -0.36±1.58% respectively. Shortening one of two strings by one module results in a power loss greater than the power contribution of the module alone (1.29 module equivalents); the impact increases through the maximum test case of a six module mismatch with a power loss equivalent to more than 11 modules. The impact of using string-end blocking diodes is presented with an emphasis at the array maximum power point and at open circuit. Implications are discussed for arrays of higher complexity.

Stimulus variation-based training enhances artificial grammar learning

The current study was designed to explore whether statistical learning ability is affected by the diversity of the stimulus set used in the training phase. The effect of stimulus diversity was assessed by controlling and manipulating the number of exposures to a given set and the number of unique strings presented to the learner during the training phase. 147 students participated in two studies. In the unvaried stimulus study, 71 participants learned the same basic set of 15 exemplars, once(15 × 1 exposure), twice (15 × 2 exposures = 30 total strings) and 3 times (15 × 3 exposures = 45 total strings). In the varied stimulus study, 75 participants learned 15, 30 and 45, all of which were unique, unrepeated exemplars. All groups were asked to classify test strings for their grammaticality following training. Results of the d’ measures in the unvaried stimulus study indicate similar performance across the groups. Conversely, the results of the varied stimulus study show that the group presented with 45 unique strings performed significantly better than the baseline group (15 strings). Analysis of the differences across the equivalent groups in the two studies (15 × 2 exposures vs. 30 unique strings and 15 × 3 exposures vs. 45 unique strings) indicates differences in performance only between the group who was presented with the same 15 strings three times and the group presented with 45 unrepeated strings. Taken together, our results shed additional light on the central role of stimulus variation in Artificial Grammar Learning.

Developing Literature Search Strategies and Strings to Identify Fate, Exposure and Physical-Chemical Property References

While the process for developing search strings for physical-chemical properties is relatively straight-forward due to availability of existing data presented in a controlled manner, identifying published fate and human environmental chemical exposure-related studies is difficult. Challenges also exist for identifying health-related studies, but controlled vocabularies for indexing and PubMed Medical Subject Headings (MeSH) help to identify such studies, while relatively fewer developed vocabularies exist for identifying fate and exposure studies. In addition, the scope of ‘exposure’ is broad and comprises several sub-categories. Provision of these search strings will facilitate and standardize the approach for systematic review of scientific evidence needed for transparent chemical assessment. To develop the search strings, a team of topic-specific experts and librarians was assembled and developed keyword lists. To create the physical-chemical string, librarians used the keyword list and a series of iterative exchanges with the expert to draft, and revise strings based on performance. For fate strings, librarians drafted strings utilizing the keyword list and analysis tools such as the Keyword Analysis Tool (KAT) and SWIFT-Review’s fingerprinting feature, and on-topic reference lists to determine performance; exposure strings will be developed in a similar manner. The quality of all test strings will be further evaluated by human manual screening of on- and off-topic search string generated results. This presentation overviews various approaches taken to develop the fate, chemical-physical property and exposure literature search strings, including development and testing of broad verses minimal search strings (where we identify terms that are unambiguous and/or necessary to retrieve the greatest number of on-topic references while minimizing retrieval of off-topic references); discusses the organization of keywords and search strings into main and subcategory headings; and outlines the process for incorporating keyword analysis tools. The recall and precision performance results of the broad versus minimal search strings are also presented.

Rhythmic Recursion? Human Sensitivity to a Lindenmayer Grammar with Self-similar Structure in a Musical Task

Processing of recursion has been proposed as the foundation of human linguistic ability. Yet this ability may be shared with other domains, such as the musical or rhythmic domain. Lindenmayer grammars (L-systems) have been proposed as a recursive grammar for use in artificial grammar experiments to test recursive processing abilities, and previous work had shown that participants are able to learn such a grammar using linguistic stimuli (syllables). In the present work, we used two experimental paradigms (a yes/no task and a two-alternative forced choice) to test whether adult participants are able to learn a recursive Lindenmayer grammar composed of drum sounds. After a brief exposure phase, we found that participants at the group level were sensitive to the exposure grammar and capable of distinguishing the grammatical and ungrammatical test strings above chance level in both tasks. While we found evidence of participants’ sensitivity to a very complex L-system grammar in a non-linguistic, potentially musical domain, the results were not robust. We discuss the discrepancy within our results and with the previous literature using L-systems in the linguistic domain. Furthermore, we propose directions for future music cognition research using L-system grammars.

Features and prevention of gas hydrate blockage in test strings of deep-water gas wells

Due to the uncertainties in formation mechanism of gas hydrate blockages in strings during the test of deep-water gas wells, inhibitors are either excessively consumed or inefficiently used when conventional prevention techniques are used. In this paper, a study was conducted on multi-phase flows, in terms of hydrate formation kinetics and hydrate particle migration and settlement kinetics. In this process, a model for quantitative prediction of hydrate blockage was built to predict when and where the blockage occurs in the strings and evaluate the severity of such blockage, in order to define the high-risk zones. Eventually, an innovative hydrate blockage prevention technique based on hydrate blockage free window (HBFW) was proposed to determine the optimal concentration and the flow rate of inhibitors. The study results are in the following four aspects. First, gas hydrates generated in the wellbore may deposit on the internal walls of strings. With the increase in thicknesses of such gas hydrate layers, the diameter of a pipe string decreases. Accumulation of gas hydrates generated around liquid film on pipe walls is the key contributor to the blockage in strings. Second, as the water depth increases or the gas production reduces, the HBFW turns to be narrower for production safety, and the time to initiate blockage is shorter. Third, application of hydrate inhibitors can effectively delay the occurrence of blockage and expand the window of safe production. Fourth, the innovative prevention technique can effectively reduce the volume and the flow rate of inhibitors (by 50% in the case study). The innovative technique effectively eliminates the problems related to the excessive consumption of inhibitors in the conventional methods and provides a valuable reference for the prevention of gas hydrates formation in deep-water gas well tests.

Prediction of wax precipitation region in wellbore during deep water oil well testing

Abstract During deep water oil well testing, the low temperature environment is easy to cause wax precipitation, which affects the normal operation of the test and increases operating costs and risks. Therefore, a numerical method for predicting the wax precipitation region in oil strings was proposed based on the temperature and pressure fields of deep water test string and the wax precipitation calculation model. And the factors affecting the wax precipitation region were analyzed. The results show that: the wax precipitation region decreases with the increase of production rate, and increases with the decrease of geothermal gradient, increase of water depth and drop of water-cut of produced fluid, and increases slightly with the increase of formation pressure. Due to the effect of temperature and pressure fields, wax precipitation region is large in test strings at the beginning of well production. Wax precipitation region gradually increases with the increase of shut-in time. These conclusions can guide wax prevention during the testing of deep water oil well, to ensure the success of the test.

AGSuite: Software to conduct feature analysis of artificial grammar learning performance

To simplify the problem of studying how people learn natural language, researchers use the artificial grammar learning (AGL) task. In this task, participants study letter strings constructed according to the rules of an artificial grammar and subsequently attempt to discriminate grammatical from ungrammatical test strings. Although the data from these experiments are usually analyzed by comparing the mean discrimination performance between experimental conditions, this practice discards information about the individual items and participants that could otherwise help uncover the particular features of strings associated with grammaticality judgments. However, feature analysis is tedious to compute, often complicated, and ill-defined in the literature. Moreover, the data violate the assumption of independence underlying standard linear regression models, leading to Type I error inflation. To solve these problems, we present AGSuite, a free Shiny application for researchers studying AGL. The suite's intuitive Web-based user interface allows researchers to generate strings from a database of published grammars, compute feature measures (e.g., Levenshtein distance) for each letter string, and conduct a feature analysis on the strings using linear mixed effects (LME) analyses. The LME analysis solves the inflation of Type I errors that afflicts more common methods of repeated measures regression analysis. Finally, the software can generate a number of graphical representations of the data to support an accurate interpretation of results. We hope the ease and availability of these tools will encourage researchers to take full advantage of item-level variance in their datasets in the study of AGL. We moreover discuss the broader applicability of the tools for researchers looking to conduct feature analysis in any field.

Dissociating Medial Temporal and Striatal Memory Systems With a Same/Different Matching Task: Evidence for Two Neural Systems in Human Recognition

ABSTRACTThe medial temporal lobe and striatum have both been implicated as brain substrates of memory and learning. Here, we show dissociation between these two memory systems using a same/different matching task, in which subjects judged whether four-letter strings were the same or different. Different RT was determined by the left-to-right location of the first letter different between the study and test string, consistent with a left-to-right comparison of the study and test strings, terminating when a difference was found. This comparison process results in same responses being slower than different responses. Nevertheless, same responses were faster than different responses. Same responses were associated with hippocampus activation. Different responses were associated with both caudate and hippocampus activation. These findings are consistent with the dual-system hypothesis of mammalian memory and extend the model to human visual recognition.

Budgerigars and zebra finches differ in how they generalize in an artificial grammar learning experiment

The ability to abstract a regularity that underlies strings of sounds is a core mechanism of the language faculty but might not be specific to language learning or even to humans. It is unclear whether and to what extent nonhuman animals possess the ability to abstract regularities defining the relation among arbitrary auditory items in a string and to generalize this abstraction to strings of acoustically novel items. In this study we tested these abilities in a songbird (zebra finch) and a parrot species (budgerigar). Subjects were trained in a go/no-go design to discriminate between two sets of sound strings arranged in an XYX or an XXY structure. After this discrimination was acquired, each subject was tested with test strings that were structurally identical to the training strings but consisted of either new combinations of known elements or of novel elements belonging to other element categories. Both species learned to discriminate between the two stimulus sets. However, their responses to the test strings were strikingly different. Zebra finches categorized test stimuli with previously heard elements by the ordinal position that these elements occupied in the training strings, independent of string structure. In contrast, the budgerigars categorized both novel combinations of familiar elements as well as strings consisting of novel element types by their underlying structure. They thus abstracted the relation among items in the XYX and XXY structures, an ability similar to that shown by human infants and indicating a level of abstraction comparable to analogical reasoning.

Implicit learning deficits among adults with developmental dyslexia.

The aim of the present study was to investigate implicit learning processes among adults with developmental dyslexia (DD) using a visual linguistic artificial grammar learning (AGL) task. Specifically, it was designed to explore whether the intact learning reported in previous studies would also occur under conditions including minimal training and instructions that do not reveal the grammatical nature of the strings. Twenty-nine (14 DD and 15 typical development (TD)) adults were presented with letter sequences in the training phase and were asked to classify the test strings for their grammaticality. The results of the d' measures in the implicit task indicated that learning had occurred for both groups, as the proportion of hits exceeded the proportion of false alarms. However, a significant difference was found between the groups in their learning measures, as TD readers performed significantly better than individuals with DD, supporting the assumption of a deficit in implicit sequential learning processes among individuals with DD. In order to examine whether the deficit found in the first experiment was indeed due to a deficit in implicit processes, a second experiment was designed in which explicit instructions were given during an AGL task. Results of the explicit task strengthen the assumption that the deficit is indeed specific to implicit sequential processes, as no difference between the groups was found when participants were aware of the existence of the grammar underlying the strings. Theoretical and clinical implications are discussed.

Helping tools for the regular expression author for test questions in LMS Moodle

Composing regular expressions for test questions is often a difficult thing for the teachers; so many teachers avoid using regular expression questions. Similar problems hinder students learning regular expressions as a part of computer science. There are many programs developed to help composing and learning of the regular expressions, but they are using different forms of regular expression visualization. The goal of this research was to compare efficiency of different forms of regular expression representation for their learning and composing, methods for linking them together and with regular expression text. A set of helping tools for regular expressions authors (as a plugin for Moodle CMS) was developed, using three form of regular expression representation: syntax tree (visualizes expression structure), explanation graph (visualizes paths of expression execution) and text description – and testing tool, showing regular expression match with test strings. Developed instruments was used by students learning regular expressions, the students fill a survey after that. Students were divided into four groups by their year of study and country. Survey shows that different group of students prefer different instruments. Most generally popular ones were explanation graph and regular testing, but even text description – a general outsider – was leading in the group of students from Africa learning in English language. The survey also shows that ability to select part of regular expression representation and see that part selected in other representations and regular expression text was very useful in linking representations together and understanding complex expressions. About a quarter of students used other regular expression construction tools before taking part in this experiment, most of them said that developed tools were better than those they used before. Several teachers, which had used regular expressions in their questions, have written reviews stating that developed instruments make learning regular expressions easier and help debug regular expressions in their questions. So, the survey of students and teachers reviews shows that system of several regular expression representations linked together by subexpression selection is more effective that any particular representation in itself; different classes of users prefer different forms of representation. Including helping tools for regular expression authors in the quiz creation software allows increasing the use of regular expressions for quiz questions and helps test and debug them.

Nonlinear dynamic analysis and fatigue damage assessment for a deepwater test string subjected to random loads

The deepwater test string is an important but vulnerable component in offshore petroleum exploration, and its durability significantly affects the success of deepwater test operations. Considering the influence of random waves and the interaction between the test string and the riser, a time-domain nonlinear dynamic model of a deepwater test string is developed. The stress-time history of the test string is obtained to study vibration mechanisms and fatigue development in the test string. Several recommendations for reducing damage are proposed. The results indicate that the amplitude of dynamic response when the string is subjected to random loads gradually decreases along the test string, and that the von Mises stress is higher in the string sections near the top of the test string and the flex joints. In addition, the fatigue damage fluctuates with the water depth, and the maximum damage occurs in string sections adjacent to the lower flex joint and in the splash zone. Several measures are proposed to improve the operational safety of deepwater test strings: applying greater top tension, operating in a favorable marine environment, managing the order of the test string joints, and performing nondestructive testing of components at vulnerable positions.

Implicit learning is order dependent.

We report two experiments using the artificial-grammar task that demonstrate order dependence in implicit learning. Studying grammatical training strings in different orders did not affect participants' discrimination of grammatical from ungrammatical test strings, but it did affect their judgments about specific test strings. Current accounts of learning in the artificial-grammar task focus on category-level discrimination and largely ignore item-level discrimination. Hence, the results highlight the importance of moving theory from a category- to an item-level of analysis and point to a new way to evaluate and to refine accounts of implicit learning.

Information theory and artificial grammar learning: inferring grammaticality from redundancy.

In artificial grammar learning experiments, participants study strings of letters constructed using a grammar and then sort novel grammatical test exemplars from novel ungrammatical ones. The ability to distinguish grammatical from ungrammatical strings is often taken as evidence that the participants have induced the rules of the grammar. We show that judgements of grammaticality are predicted by the local redundancy of the test strings, not by grammaticality itself. The prediction holds in a transfer test in which test strings involve different letters than the training strings. Local redundancy is usually confounded with grammaticality in stimuli widely used in the literature. The confounding explains why the ability to distinguish grammatical from ungrammatical strings has popularized the idea that participants have induced the rules of the grammar, when they have not. We discuss the judgement of grammaticality task in terms of attribute substitution and pattern goodness. When asked to judge grammaticality (an inaccessible attribute), participants answer an easier question about pattern goodness (an accessible attribute).

What Influences Children's Conceptualizations of Language Input?

Children learning language conceptualize the nature of input they receive in ways that allow them to understand and construct utterances they have never heard before. This study was designed to illuminate the types of information children with and without specific language impairment (SLI) focus on to develop their conceptualizations and whether they can rapidly shift their initial conceptualizations if provided with additional input. In 2 studies, preschool children with and without SLI were exposed to an artificial language, the characteristics of which allowed for various types of conceptualizations about its fundamental properties. After being familiarized with the language, children were asked to judge test strings that conformed to the input in 1 of 4 different ways. All children preferred test items that reflected a narrow conceptualization of the input (i.e., items most like those heard during familiarization). Children showed a strong preference for phonology as a defining property of the artificial language. Restructuring the input to the child could induce them to track word order information as well. Children tend toward narrow conceptualizations of language input, but the nature of their conceptualizations can be influenced by the nature of the input they receive.

Reservoir Testing System Evolves to Meet New Frontier Challenges

Technology Update As today’s deep wells challenge the bounds of pressure and temperature, accurate reservoir testing has become essential to mitigate production risk. The information contained in a series of downhole pressure transient measurements and representative reservoir fluid samples can make or break a prospect’s potential. The consistent and accurate acquisition of this information requires the precision instrumentation and functionality of a drillstem testing system. Whereas excellent downhole logging instruments can describe the near-borehole regions, only a drillstem test can reach deeply into the reservoir to discover boundaries, faults, and fractures; confirm volumetric reserves estimations; and acquire the cleanest, most representative fluid samples to provide accurate fluid phase behavior, physical properties, and com-positional analyses. Safety, Reliability, and Efficiency The Schlumberger Quartet high-performance downhole reservoir testing system combines four proven downhole technologies into a package that can isolate the zone, control flow, measure pressure and temperature, and acquire multiple single-phase reservoir fluid samples on a single trip into the well. The system provides enhanced safety, increased efficiency, and improved reliability to testing operations. Compared with conventional downhole test strings, the system functions with a 35% lower tool operating pressure, 50% fewer seals, and 60% fewer connections, while requiring 90% less nitrogen. The system is four times shorter than a conventional tool string because it eliminates the requirement for a safety joint, jar, slip joints, and drill collars. Despite its smaller size, the system is sufficiently durable to permit perforating guns to be run below the packer and fired without incurring damage to the tools or impairing their accuracy or integrity. The system also includes a below-packer circulating valve to allow a more efficient well kill following the test, which is especially important when testing gas wells. Each of the four tools that make up the downhole reservoir testing system operates individually and collectively to perform the test. The CERTIS high-integrity reservoir test isolation system delivers production-quality well isolation. The isolation system combines the features of a retrievable drillstem test packer with a hydraulically set permanent packer, making the safety joint, jar, slip joints, and drill collars unnecessary. Because the system is actuated by annulus pressure, no rotational or set down forces are required.

Lifshitz singularities

Lifshitz spacetimes are possible gravitational duals to strongly coupled field theories with an anisotropic scaling symmetry. These spacetimes however, have a null curvature singularity. We find that higher dimensional embeddings of Lifshitz also have a similar singularity. We study the propagation of test strings in this background and find that they become infinitely excited if they try to propagate through the singularity. This means that the Lifshitz geometry is unstable and will receive large corrections in string theory.

Toroidal spiral Nambu-Goto strings around higher-dimensional black holes

We present solutions of the Nambu-Goto equation for test strings in a shape of toroidal spiral in five-dimensional spacetimes. In particular, we show that stationary toroidal spirals exist around the five-dimensional Myers-Perry black holes. We also show the existence of innermost stationary toroidal spirals around the five-dimensional black holes like geodesic particles orbiting around four-dimensional black holes.