Continuous psychophysics for two-variable experiments; A new “Bayesian participant” approach

The present investigation was designed to study the effect of area and exposure time of stimulus upon the fusion time of visual sensation. In the dark room two flashes of light were presented successively at an identical location for equal brief durations. Two kinds of thresholds were measured. One of them Was the threshold of fusion and this was defined as. the longest time internal between the two stimuli which produced a single impression (tf), and the other was the threshold of separation and this was defined as the shortest time interval which produced an impression that the second stimulus appeared after the complete disappearance of the first stimulus, i. e., the shortest time interval for perceiving dark interval between the stimuli (ts). So the present experiment was different from the flicker experiment in several points. Using the monocular and foveal vision, the following results were obtained.1. As the area of stimulus was enlarged, ts became smaller. But after ts reached its minimum value at some area, it remained approximately constant within some range of area, then it increased when the area was further enlarged. The value of tf was much smaller than ts, and, in addition, tf became smaller when the stimulus area was enlarged.2. As the exposure time of stimulus was lengthened, ts became smaller.3. Regardless of the length of the exposure time, tf remained approximately constant.4. Presenting two stimuli in differentloci successively, the threshold of simultaneity (tsi) was measured for comparable time interval to the above tf. The threshold of simultaneity was defined as the longest time interval that both stimuli appeared simultaneously. It was found that tsi increased in proportion to the logarithm of the visual angle between the stimuli within 19 degrees of visual angle. When both the visual angle and the perceived distance between the stimuli were held constant, the value of tsi remained the same, regardless of the variation in the objective distance between the stimuli on the one hand and the observing distance on the other.

STIMULUS EXPOSURE TIME AS A FACTOR IN SERIAL LEARNING IN AN AGED SAMPLE.

The purpose of the present study was to further clarify the role of stimulus exposure time as a variable which affects responses to projective material. Presentation of the standard Rorschach cards over a series of exposure times, ranging from .03 sec. to unlimited exposure, constituted a systematically controlled range of perceptual conditions with stimuli known to have rich and useful personality correlates. In an earlier tachistoscopic smdy Stein (1949) demonstrated different patterns of response as a function of exposure time of Rorschach cards; however, the small sample used (17 Ss who responded under ascending exposure order) limited the generality of his results, and no evaluation of perceptual modes, independent of the experimental conditions, was reported. Stein's study explored the clinical usefulness of a tachistoscopic Rorschach technique by applying it to the analysis of several individual cases. A later study by Stein and Meer (1954) pointed to the usefulness of the tachistoscopic Rorschach technique in discriminating between Ss of high and low creative ability. In the view of chis author, the experimental design used in the present study invites consideration of what perceptual processes may accompany the physically manipulated conditions of minimal and sustained exposure of the stimulus. When an external stimulus is exposed very briefly, the opportunity for the perceiver to base his reactions on an interaction with the stimulus is relatively limited, and he is thereby forced to rely largely upon subjective factors and his immediate, brief perception of the stimulus. Some of the contributing factors which the perceiver may bring to the experimental situation are those of cognitive structure, personality structure, motivational states, and past learning. As exposure time of the external stimulus is increased, more time is available during which interaction between perceiver and stimulus can occur. As there is increased opportunity to investigate the stimulus at slower tachistoscopic speeds, more information can be obtained from the sc~mulus, and there is more time for corrections in perception. While the experimental situation thus varies systematically in the opportunity for interaction, it does not of course follow that all Ss will respond equally to the increased possibilities for interaction with the stimulus at longer exposure times. The present article will be limited to a report and discussion of the more formal aspects of Ror'This article is based upon a doctoral dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the School of Education of New York University, 1956. The author is indebted to Professor John 1. Sullivan for his direction of the research. An abridged account of the study was presented at the Sixty-Sixth Annual Convention of the American Psychological Association, 1958.

A short term recognition memory task which varied the number of letters distinguishing target and comparison stimuli was used to assess the ability of prereaders and beginning readers to utilize graphic information in a three letter graphic pattern. In Experiment 1 the Exposure Time of the target stimulus and the Retention Interval were varied. Results indicated that children were not able to process the graphic pattern as a single unit. Children based their same-different judgments on only limited graphic information and displayed clear saliency effects of the initial letter position. In fact, stimuli distinguished by an initial letter difference were more discriminable than those which differed in both middle and final letter positions. An Exposure Time × Position interaction supports the interpretation that position saliency is in part the result of serial encoding. Contrary to some explanations of position saliency, both readers and non-readers demonstrated the effect. In Experiment 2, beginning kindergarten children failed to demonstrate an effect of position. These studies indicate that early reading or prereading activities result in serial encoding strategies.

Variations in the Visual Threshold THE problems of visual research discussed in this lecture mainly concern the sensitivity of the retina. A very general test of retinal sensitivity is the determination of the threshold increment, or, briefly, the threshold. The eye views a given distribution of brightness—which may be varying with time in a prescribed way—and, at a given moment, a small additional light stimulus is applied at a particular point in the visual field. By repeated trials with different intensities of the additional stimulus, the critical intensity can be determined at which the observer sees the stimulus on fifty per cent of occasions. This threshold increment, or better, its reciprocal, provides a measure of the sensitivity of a given part of the retina at a given time. It can be determined under a wide range of conditions, and by varying the angular size, exposure time and colour of the test stimulus the response can be made to depend in different degrees on different mechanisms in the retina.

MANIPULATION OF THE ANNUAL GROWTH CYCLE OF BLUEBERRY USING PHOTOPERIOD

We present an efficient algorithm for approximating huge general\n volumetric data sets, i.e.~the data is given over arbitrarily shaped\n volumes and consists of up to millions of samples. The method is based\n on cubic trivariate splines, i.e.~piecewise polynomials of total\n degree three defined w.r.t. uniform type-6 tetrahedral partitions of\n the volumetric domain. Similar as in the recent bivariate\n approximation approaches, the splines in three variables\n are automatically determined from the discrete data as a result of a\n two-step method, where local discrete least\n squares polynomial approximations of varying degrees are extended by\n using natural conditions, i.e.the continuity and smoothness properties\n which determine the underlying spline space. The main advantages of\n this approach with linear algorithmic complexity are as follows: no\n tetrahedral partition of the volume data is needed, only small\n linear systems have to be solved, the local variation and\n distribution of the data is automatically adapted,\n Bernstein-B{\\'e}zier techniques well-known in Computer Aided\n Geometric Design (CAGD) can be fully exploited, noisy data are\n automatically smoothed. Our numerical examples with huge data sets\n for synthetic data as well as some real-world data confirm the\n efficiency of the methods, show the high quality of the spline\n approximation, and illustrate that the rendered iso-surfaces inherit\n a visual smooth appearance from the volume approximating splines.

Seismic interpretation is an essential factor in the success of field development projects because it allows geologists and engineers to better understand subsurface formations and identify potential resources; however, noisy seismic data, especially in regions with complex geological structures, frequently hinder this process. Such noise emerging from equipment limitations, environmental interference, and inherent geological complexities can obscure essential geological features, making accurate subsurface imaging challenging and reducing the effectiveness of traditional interpretation methods. This paper presents a machine learning (ML) method to enhance the conditioning of 2D and 3D post-stack seismic data by targeting noise and migration artifacts. These issues are often responsible for compromising the quality of seismic data sets. The method this paper presents leverages convolutional neural networks (CNNs) to identify and correct spatial inconsistencies within the data. With minimal preprocessing, requiring only the conversion of data into a 3D NumPy array format, this approach simplifies the workflow while improving data clarity and accuracy. Early statistical analysis of outliers and data normalization provides the ML model with stable inputs, allowing it to iteratively train on raw data and infer the original signal patterns in an unsupervised manner without the need for labeled data sets. The model outputs a conditioned version of the seismic data, significantly reducing noise while preserving critical geological features. The results demonstrate that ML seismic conditioning improves fault imaging, horizon continuity in areas with low signal-to-noise ratios (SNR), and localized smoothing without compromising resolution. Furthermore, the method presented in this paper retains signal fidelity and relative amplitude strengths, ensuring that geological interpretations remain accurate and reliable. By automating the traditional manual task of data conditioning, the proposed solution optimizes interpreter workflows, allowing them to focus on higher-level geological analysis and decision-making. This approach ultimately increases the accuracy of subsurface interpretations and resource exploration, improving the overall quality and efficiency of seismic interpretation projects. In addition, for 2D seismic, traditional methods of denoising rely on expert judgement using tools such as f-x deconvolution. 2D CNNs offer an efficient alternative, especially when training data can be synthesized and leveraged in supervised learning. This method can help the CNN identify and remove noise while preserving pertinent subsurface structures. This paper presents a 2D CNN architecture containing a model trained with synthetic seismic data to improve SNR of field seismic data; hence, interpretation.

A class-specific feature selection and classification approach using neighborhood rough set and K-nearest neighbor theories

Micro-blogging is a new form of social communication that encourages users to share information about anything they are seeing or doing, the motivation facilitated by the ability to post brief text messages through a variety of devices. Twitter, the most popular micro-blogging tool, is exhibiting rapid growth [3]: up to 11% of online Americans are using Twitter by December 2008, compared to 6% in May 2008. Due to its nature, micro-blogosphere has unique features: (i) It is a source of extremely up-to-date information about what is happening in the world; (ii) It captures the wisdom of millions of people and covers a broad range of domains. These features make micro-blogosphere more than a popular medium of social communication: we believe that it has additionally become a valuable source of extremely up-to-date news on virtually any subject of user interest. Making use of micro-blogosphere in this new role we meet the following challenges: (A) Since any given subject is generally mentioned in the micro-blogging stream on the continuous basis, a method is needed for locating periods of news on this subject. (B) Additionally, even for such periods, stream filtering is required for removing noise and for extracting messages that best describe the news. To address these challenges we make and exploit the following observations: (A) For an arbitrary subject, events that catch user interest gain distinguishably more attention than the average mentioning of the subject resulting in message activity bursts for it. (B) Most of the messages in an activity burst describe common event in close variations - either rephrased or "retweeted" between the users. We demonstrate TweetSieve - a system that allows obtaining news on any given subject by sifting the Twitter stream. Our work is related to frequecy-based analysis applied to blogs [1], but higher latency and lower coverage in blogs makes the analysis less effective than in case of micro-blogs. In TweetSieve demo, the user is able to express the subject of her interest by an arbitrary search string. The system shows the period of events occuring for the subject and outputs tweets that best describe each of the events. Figure 1 shows a screenshot of the system for "Semantic search" as a sample subject. The underlying process consists of two steps: Identifying activity bursts. Counting the messages matching the search string in the stream over time, the frequency curve is constructed. Activity bursts in the curve are identified by taking the periods of frequency exceeding the standard deviation from the average. Selecting messages that best describe news events. For the set of all messages matching the search string in an activity burst, we apply the message-granular variation of our keyphrase extraction algorithm [2] that is specifically suited to efficiently filtering noisy data. The algorithm clusters messages with respect to their similarity to each other and chooses central messages from the most dense clusters. As the similarity measure we use Jaccard coefficient for the "bag of words" representation of messages. The demonstration illustrates the potential of our approach in bringing news acquisition to a new level of promptness and coverage range.

The objective of this study was to compare the laboratory slaking behavior of common clay-bearing rocks to their slaking behavior under natural climatic conditions observed during a 1-year experimental study. Five-cycle slake durability tests were performed in the laboratory on five claystones, five mudstones, five siltstones, and five shales. Twelve replicate specimens of each of these 20 rocks were also exposed to natural climatic conditions for 12 months. After each month of exposure, one replicate specimen of each rock was removed from natural exposure and its grain size distribution was determined. The results of laboratory tests and field experiment were compared in terms of 1st, 2nd, 3rd, 4th, and 5th cycle slake durability indices (Id1, Id2, Id3, Id4, Id5), grain size distribution of slaked material, and disintegration ratio (D R), where D R is the ratio of the area under the grain size distribution curve of slaked material for a given specimen to the total area encompassing all grain size distribution curves of the specimens tested. Correlations of Id1, Id2, Id3, Id4, and Id5 with D R values for laboratory specimens exhibit R 2 values of 0.87, 0.88, 0.83, 0.75, and 0.70, respectively. However, the relationship between Id2 and D R, determined after 1, 3, 6, and 12 months of natural exposure, becomes weaker with increasing time of exposure, with R 2 values of 0.65, 0.63, 0.63, and 0.25, respectively. The fifth-cycle slake durability index (Id5) for laboratory tested specimens shows a better correlation with D R values for naturally exposed specimens (R 2 up to 0.80). A comparison of grain size distribution curves of slaked material for laboratory specimens, after the 2nd cycle slake durability test, with those of specimens exposed to natural climatic conditions shows that the laboratory test underestimates the field durability for claystones, and overestimates it for siltstones.

In field development and reservoir surveillance planning, there is an absolute need to obtain reliable values for reservoir pressures, productivity indexes and other values on a continuous basis so that planning can be done reliably and production / recovery can be optimized. However, continuous data acquisition is often where we stumbled due to a combination of economic, operational/logistical constraints. An alternative is to derive these key parameters from surface data using dynamic well modeling techniques. Subsurface data acquisition will be replaced by surface data acquisition, reducing the number of well interventions and data acquisition costs. The major assumption in current PVT correlations in dynamic well modeling application is instantaneous transformation of one phase (gas) into another phase (oil). During shut-in, this assumption leads to inaccurate modeling of the gas/liquid distribution in the well and hence, an incorrect prediction of interphase level, in-situ density and pressure distribution in the well. The objectives of this research is to improve the current dynamic well modeling technique by incorporating the mass transfer rate model into current PVT model for a reliable well shut-in status description. This is a relatively new and unexplored technical method, which increases the understanding of well behavior. This novel PVT model is able to determine an accurate volume of each fluid phase at any node in the wellbore by incorporating the fluid segregation, mass transfer rate and fluid ingress in the reservoir during shut-in. This better description of wellbore dynamic behavior improves the accuracy of dynamic well modeling ensuring a reliable downhole data determination. This paper presents a status update in well performance modeling and the proposed scheme in developing the novel PVT model. A number of engineering conceptions were reviewed and all the elements that become the foundation of the well bore transient mechanics were discussed.

The development of methods for investigation of tactile perception under natural conditions is justified by the observation that the sensitivity of a freely exploring body part often exceeds the sensitivity during passive stimulation (Katz, 1925). This paper (a) suggests methods for selective investigation of size, shape, and surface perception under natural conditions, and (b) presents some principles of quantification when objects are used as tactile stimuli. By means of these methods and principles, it is possible to construct any stiff object and to achieve a complete description of the stimulus variables.

This paper suggests that the mechanism that controls resistance of plants to oxidant pollutants may be similar to the one that controls resistance to other extremes in environmental factors. From the literature the following generalizations can be made in regard to the factors that affect the sensitivity of plants to oxidant air pollutants during growth: plants are more sensitive when grown under a short photo-period, a long dark period prior to exposure increases sensitivity; plants grown under low light intensities are more sensitive to ozone and less sensitive to PAN; low temperatures for one to several days prior to exposure reduce sensitivity; plants grown under drought conditions are less sensitive; plants grown under relatively low fertility levels are more sensitive. Sensitivity at time of exposure increases with increasing light intensity. Sensitivity of plants exposed under natural conditions is affected more by light intensity than by temperature. Temperature has an inverse effect on sensitivity, when plants are exposed under controlled lighting conditions. High carbon dioxide levels, at time of exposure, reduce sensitivity. Plants exposed under any soil conditions that produce a water stress in the plant show an increased resistance. Plant sensitivity, at time of exposure, increases with an increase inmore » humidity. Injury from PAN is mediated by a light-sensitive system within the plant. Sulfur dioxide reacts synergistically, with both ozone and nitrogen dioxide, on sensitive plant tissues. 101 references.« less

Leaching of ions from foliage of black gum (Nyssasylvatica Marsh.), chestnut oak (Quercusprinus L.), and white pine (Pinusstrobus L.) in response to increasing exposure time to and concentration of H+ was examined in a laboratory study. Ten individual leaves and needle bundles were exposed to H+ solutions at pH 3.0, 4.0, and 5.6 for periods of 5, 50, 500, and 1000 min. Increases in the removal of Ca2+ and Mg2+ from all species tested were strongly related to increases in experiment duration and H+ concentration, confirming the role of ion exchange in the removal of these ions from the forest canopy. Removal of Na+ and K+ did not appear to be strongly influenced by ion exchange. Positive relations between SO42− and H+ (and presumably Cl−) for the deciduous species suggest that anion exchange may be involved in the removal process. Given the relatively small number of anion exchange sites on cuticles, and because SO42− is the primary anion in both rain and throughfall, anion exchange is not likely to contribute significant amounts of anions under natural conditions. It is difficult to extrapolate results from an experiment of this type to what might be expected under natural conditions. However, the response of whole leaves and needles fits that expected based on the ion selectivity of the cuticle as a carboxylic acid ion-exchange medium and holds promise for understanding the processes involved in ion leaching from forest canopies.