Reviewerly/exHarmony huggingface dataset:
Contribution of stereopsis and motion parallax to fear response in the pit room environment

Stereopsis and active motion parallax are two of the main perceptual factors provided by head mounted displays to create a sense of presence in virtual environments. However, their relative contribution to create the sense of presence is not clear and existing results are somewhat controversial. Here, we study the contribution of stereopsis and active motion parallax using variants of the classic pit room paradigm in two experiments. In the first, participants were required to cross a deep abyss between two platforms on a narrow plank. They completed the task under three experimental conditions: (1) Standard VR (both motion parallax and stereopsis were available); (2) The lateral component of motion parallax was disabled; (3) Stereopsis was disabled. Participants responded to a presence questionnaire after each condition and their electrodermal activity (EDA) was recorded as a measure of stress and anxiety in a threatening situation. Results revealed a main effect of condition and the importance of motion parallax (F[2,54] = 6.71; p< 0.005). Questionnaire results, on the other hand, did not show an effect of experimental condition (F[2,54]=0.04; n.s.). In the second experiment, we applied a similar paradigm in a less stressful context. Participants were standing on the ledge over the pit and dropped a ball trying to hit a target on the ground. Experimental conditions and dependent measures were similar to experiment 1. Both EDA (F[2,36] = 4.70; p< 0.05) and presence questionnaire (F[2,36] = 5.73; p< 0.01) revealed a main effect of condition. Motion parallax affected the EDA and questionnaire scores more than stereopsis. The results from this study suggest that in VR, motion parallax is a more efficient depth cue than stereopsis in terms of fear response which was measured by EDA. Presence questionnaires also showed the importance of motion parallax in the second experiment.
Knowledge Map Analysis of CBR-Based on CiteSpace

CBR is an important branch in the field of artificial intelligence, which is a case-based reasoning system. Rational use of CBR can effectively solve problems such as emergency decision-making, disaster management, medical diagnosis, etc., so the research on CBR has important significance. To show CBR research focus problem and digging a new research direction at the same time, CBR related literatures were analyzed by CiteSpace V software. Finally, we get the information of co-occurrence of research institutions, co-citation of authors, and co-occurrence network of key words. The results show that :1. The institutions with the highest number of published articles are all universities; 2. The articles of Zhiwei Ni, Jianyang Li and Huiting Liu are cited more frequently; 3. The top high-frequency keywords are case-based reasoning, fault diagnosis, expert system, case retrieval, rule reasoning, etc., which are research hotspots
Pick up your bricks! Interactive visual search in a familiar real-world environment

Research on visual search is overwhelmingly limited to participants sitting in front of a computer screen pressing buttons. But how well do these effects transfer to real-life situations? In this series of experiments, we gradually investigated the feasibility of using an interactive environment to learn about how people search. We used a real-world search task that almost everybody has been familiar with since childhood: Finding specific LEGO bricks among many distractors. In the first experiments, the bricks were mounted on gray plates to mirror classic computerized visual search tasks. A specific target brick was contained on each plate multiple times. As expected, the results indicate that participants performed worse when they had to search for a feature conjunction and when the target was less discriminable from the distractors. In the next experiments, the to-be-picked-up target bricks (and up to 200 distractors) were poured onto trays. The results show that the size of the target brick was the major indicator for search difficulty. Target shape and color had only limited influence on performance. In the final set of experiments, participants were instructed to assemble four similar objects out of multiple different bricks. This included a search for multiple different target bricks simultaneously. First results indicate that participants first looked for multiple target bricks at once and picked up all they could find. Then, they specifically looked for missing pieces to assembled one object after the other. Overall, this setup proved to be valuable to learn about participants’ every-day search strategies. We are convinced that using the LEGO environment will prove to be an important method in future visual search research as it offers the applicability and generalizability of familiar real-world environments while also providing a standardized search space.
Visual Analytics for Congestive Heart Failure Mortality Prediction.

Several indices exist to classify Congestive Heart Failure (CHF) patients' propensity for early mortality; however, they are primarily based on limited data and are not intuitive to use at the point of care. We investigate a novel, data-driven, risk assessment and visualization approach to investigate mortality prediction of CHF patients using data retrieved from an intensively digitized hospital's data repository. Combining well-known, computationally efficient, dimensionality reduction (DR) methods with 2-d information visualization, the method classifies and visualizes CHF patients into high and low risk groups, contextualized by the factors driving their classification. The DR method performed similar to logistic regression (LR), but visualized the classification and its significant factors at the population level, individual level and the potential impact of interventions for an individual patient. These are encouraging results in favor of the proposed visualization approach, and contributes to the current focus on advancing patient care via large-scale visual analytics.
Introduction to C

The C programming language was created in the 1970s, yet it is still in extensive use today and is the basis of many other languages. For this reason I have used C as the language for the solution of the numerical problems demonstrated in this book.
Neural reconstructions of attended object features using fMRI and EEG

Spatial attention is thought to play an essential role in selecting relevant information and ignoring irrelevant information. But spatial attention is dynamic, constantly shifting and splitting across multiple objects and locations. How can we measure neural representations of visual features under conditions of dynamic attention, and how do these measurements link with behavior? Both fMRI (e.g., Brouwer & Heeger, 2009) and EEG (e.g., Garcia, Srinivasan & Serences, 2013) have recently been used to reconstruct object features. Here we ask whether these reconstruction techniques can be applied to behaviorally-relevant, attended features (from a multi-item display), and whether the quality of these reconstructions are linked to behavior. In an fMRI task, subjects were briefly shown an array of three colored and oriented gratings. Subjects were then asked to report either the color or orientation of the grating at a spatially pre-cued location. To manipulate dynamic attention, some trials included a second spatial pre-cue at a different location, such that subjects had to covertly shift attention and report the features of the object at the new location. In a similar EEG task, two gratings were shown on the screen, and subjects were asked to covertly attend to one of them to detect subtle orientation changes. Using both techniques, we were able to reconstruct the features of the attended item by applying an inverted encoding model (e.g., Sprague & Serences, 2015). In particular, we achieved reliable feature reconstructions only when the feature was relevant to the current task. Moreover, fMRI neutral reconstruction performance was linked to trial-by-trial behavioral errors. These results emphasize the role of focused spatial attention in the feature-binding process and illustrate the potential of these techniques to provide neural measurements of attended feature representations under dynamic conditions without requiring behavioral responses.
Webometric Evaluation of the Websites of the Indian Premier League (IPL) Teams

The study focuses on the ranking of the websites of the IPL franchises as well as the overall evaluation of those websites. Authors have has been found that according to the Simple Web Impact Factor (SWIF) ranking CSK holds the numero uno status with SWIF of 0.6454.
Awareness, perception and use of social networking sites among library professionals and Semi-Professionals: A case study

Academic libraries are playing an important role in promoting library resources and services. Awareness on Social Networking Sites and their use are very much essential to the library professionals and semi- professionals to promote the library resources and services and for maximum utilization of the same. Manipal Academy of Higher Education (MAHE) has 12 libraries and the current study is limited to 10 libraries. The main objective of the study was to study the awareness, perception and use of Social Networking Sites among library professionals and semi-professionals at MAHE libraries. Questionnaire method was used in the study. It is observed from the study that all the respondents are having awareness about social networking sites and have good perceptions about SNSs. The study recommended MAHE libraries to take the initiative in including social networking sites on their library web sites for building a network within themselves as well as with users to maximize the use of library resources and services and to increase the visibility of the libraries.
PROFIL TINGKAT PENGETAHUAN GURU BIOLOGI DI SMPN SEKOTA TERNATE TENTANG SINDROM DISLEKSIA UMUM PADA SISWA SMP

Descriptive survey research has been carried out on the analysis of the level of knowledge of Biology teachers at junior high School in Ternate City about Dyslexia syndrome in junior high school students. The objective  of this study was to determine the profile of the level of knowledge of Biology teachers at the SMP in Ternate about dyslexic syndrome in middle school students. The results of this study indicate that in general the level of knowledge of Biology teachers about general Dyslexic syndrome in junior high school students in Ternate in the category of Very Good, this can be seen in the teacher's answer choices most answered on a scale of 5 (strongly agree) as much as 61.3%, scale 4 (agree) as much as 24%; scale 3 (quite agree) of 8.1%; and scale 2 (disagree) of 5.6% and scale 1 (strongly disagree) of 1%. The results of this study are expected to be taken into consideration in the handling of students with special needs appropriately especially for students with problems reading difficulties at the junior high school level. Keywords: profile, knowledge, syndrome, dyslexia, difficulty, reading
Natural Language Generation for Non-Expert Users

Motivated by the difficulty in presenting computational results-especially when the results are a collection of atoms in a logical language-to users, who are not proficient in computer programming and/or the logical representation of the results, we propose a system for automatic generation of natural language descriptions for applications targeting mainstream users.Differently from many earlier systems with the same aim, the proposed system does not employ templates for the generation task.It assumes that there exist some natural language sentences in the application domain and uses this repository for the natural language description.It does not require, however, a large corpus as it is often required in machine learning approaches.The systems consist of two main components.The first one aims at analyzing the sentences and constructs a Grammatical Framework (GF) for given sentences and is implemented using the Stanford parser and an answer set program.The second component is for sentence construction and relies on GF Library.The paper includes two use cases to demostrate the capability of the system.As the sentence construction is done via GF, the paper includes a use case evaluation showing that the proposed system could also be utilized in addressing a challenge to create an abstract Wikipedia, which is recently discussed in the BlueSky session of the
A Study on the Pipeline Management System of Petrochemical Industrial Complex in Yeosu

This study suggests ways to identify and reduce the risk to the petrochemical industry in Yeosu. In particular, it has a higher density of facilities than other petrochemical industrial complexes. In addition, Jeonnam province has the highest number of
Theory of Covert Search in Noise Backgrounds Correctly Predicts Asymmetrical Spatial Distributions of Misses and False Alarms

Searching the environment in a fast and efficient manner is a critical capability for humans and many other animals. Normally, multiple fixations are used to identify and localize targets. However, in the special case of covert search the target must be identified and localized within a single fixation. Here we present a theory of covert search that takes into account the statistical variation in background images, the falloff in resolution and sampling with retinal eccentricity, the increase in intrinsic location uncertainty with retinal eccentricity, and the prior probability of target presence and target location in the image. The computational steps of the theory are as follows. First, the effective prior probability distribution on target location is computed from the prior and the intrinsic location uncertainty. Second, the effective amplitude of the target (also dependent on retinal eccentricity) is computed and the target (if present) is added to the background. Third, template responses are computed at each image location by taking the dot product of a template (having the shape of target) with the image and then adding a random sample of internal noise. Fourth, the responses are correctly normalized by the sum of the internal noise variance and the estimated variance due to external factors (the background statistics). Fifth, the normalized responses are summed with the log of the effective prior on target location to obtain values proportional to the posterior probability. If the maximum of these values exceeds a criterion, the response is that the target is present at the location of the maximum. The theory predicts that i) misses occur more often than false alarms, ii) misses occur further in the periphery than false alarms, and iii) these asymmetries decrease with increasing target amplitude. Preliminary results show that the theoretical and human spatial distribution of errors are similar.
What makes an image interesting?

At VSS2018, we demonstrated that of the various scene categories (aerials, cityscapes, indoors, landscapes, people), observers rated landscapes as most interesting and indoor scenes as least interesting. Here we ask: are there eye-movement proxies of viewer interest, what makes an individual scene interesting to a viewer, and can information present in the scene predict its interestingness? We studied eye scan patterns while 44 observers free viewed scenes and found that the average duration of fixations best matched subjective interest ratings, more so than number of fixations/saccades, average saccade duration or viewing duration. New stimuli grab our attention. Does presenting a scene from a new, altogether different category spike viewer interest? For this, 68 observers viewed ten scenes of people, then one scene from a non-people category, and the sequence was repeated three additional times (44 scenes total). Interest ratings of the intermittently shown non-people scenes were significantly higher than those of the more frequently shown scenes of people. In a separate experiment, scenes of people were replaced by landscapes with a similar 10:1 landscape to non-landscape ratio. Interest ratings (63 observers) of the intermittently shown non-landscapes were significantly lower than those of the more frequently shown landscapes. In summary, novelty of image category does not spike viewer interest, but rather the actual image category does. Note that viewing durations were not commensurate with interest ratings. Are more complex images more interesting? We presented two scenes side by side (40 pairs) and had 40 observers free view the scenes while they were displayed for a fixed duration. Each pair was carefully chosen so that the two images differed in Jansen-Shannon complexity. More time was spent viewing the more complex image of the pair on ~70% of trials. Further analysis is ongoing.
Research on Harmonious Autonomous Learning in Vocational Education

In the process of vocational education, the use of independent learning can be helpful to the completion of teaching tasks and the realization of the goal of cultivating innovative talents to a certain extent. To properly deal with the relationship between various elements in the process of autonomous learning is to take students as the main body and harmoniously deal with the teaching process such as learning methods, learning contents, learning situations and achievement evaluation methods, which will help improve the learning effect and innovation ability of students. In addition, how to treat the role and status of teachers, the utilization of learning resources and the use of learning incentive methods in the process of autonomous learning are also important factors in the realization of harmonious autonomous learning.
Costs of attentional set-shifting during dynamic foraging, controlled by a novel Unity3D-based integrative experimental toolkit

Introduction: There is an increasing demand for experiments in which participants are presented with realistic stimuli, complex tasks, and meaningful actions. The Unified Suite for Experiments (USE) is a complete hardware and software suite for the design and control of dynamic, game-like behavioral neuroscience experiments, with support for human, nonhuman, and AI agents. We present USE along with an example feature-based learning experiment coded in the suite. Methods: USE extends the game engine Unity3D with a hierarchical, modular state-based architecture that supports tasks of any complexity. The hardware, based around an Arduino Mega2560 board, governs communication between the experimental computer and any experimental hardware. Participants in our task had their eyes tracked as they navigated via joystick through a virtual arena, choosing between two objects on each trial, only one of which was rewarded. Objects were composed of multiple features, each with two possible values. Each context, signaled by the pattern of the floor, had a single rewarded feature value (e.g. red objects might be rewarded on a grass floor, pyramidal objects might be rewarded on a marble one). Results: USE’s hardware enables the synchronization of all data streams with precision and accuracy well under 1 ms. Gaze was classified into behaviors (e.g. fixations/saccades) which displayed appropriate characteristics (e.g. velocities/magnitudes), and demonstrated ecologically meaningful characteristics when re-presented over task videos. Rule learning was all-or nothing, moving from chance to near-perfect performance in one or two trials. Participants displayed standard effects of set switching, including worse performance when contexts differed from the previous trial, and when rules involved an extra-dimensional shift from the previous block. Conclusions USE enables the creation and temporally-precise reconstruction of highly complex tasks in dynamic environments. Our example task shows that costs associated with attentional set-switching generalize to such dynamic tasks.
Information processing architectures across the visual field: an EEG study

How people combine and utilize information from different sources during cognitive processing has always been an interesting topic in visual research. Frameworks such as Systems Factorial Technology (SFT) have been developed to study this process. By using a variety of non-parametric analyses such as mean interaction contrast and survivor interaction contrast, SFT can distinguish between types of information processing architectures (mainly parallel and serial) as well as stopping rules (mainly exhaustive and self-terminating). However, most of these frameworks utilize behavioral data for model building and psychophysiological activities underlying the models are not commonly examined. The present study aims at both extending SFT with similar visual stimuli presented in bilateral visual fields, and examining the brain activities by looking at ERPs and continuous EEG data. We expect to see we expect to see different patterns of architectures and stopping rules when the location of stimuli varies, and we also expect to see different patterns of psychophysiological activities from different conditions.
Prescription Basket Analysis: Identifying Association Rule Among Drugs in Prescription of Dentist in Bhubaneswar City

Amount of clinical and diagnosis data produced within the healthcare industry has grown to be vast, and thus, it provides a prospective for data mining research. Data mining is the process of pattern discovery and extraction which originally used in the field of marketing and now been used effectively in other fields such as bioinformatics, immunology, and nuclear science. Discovery of knowledge has potentially possibilities and thus will enhance the quality of health care to patients. Drug manufacturer needs to use the information efficiently and to discover patterns from large data and build predictive models. The objective of prescription basket analysis is to identify association rules between groups of drugs prescribed by dentists in their prescription. The data have been collected from the prescription of the dentists from different dental colleges as well as the dental clinics. Apriori algorithm applied to data collected from the prescriptions by dentists, and various association rules were found from the prescription data. It can provide information to pharmacy store to understand the prescription behavior of dentists which can help the pharmacy store in correct decision making in keeping their inventory. The research tried to discover the prescription behavior and association between drugs. Based on the result, the manufacturers can redesign their marketing strategy in the intention of improving patient care and thus decreasing healthcare cost. The results will reveal valuable insights into the association between drugs prescribed by dentists.
Reform of Embedded Software Training System Based on Cultivation Mode for Engineering Talents

Of general standards for engineering education certification, there are 8 items related to "complex engineering problems", so the basic orientation of undergraduate engineering education is to cultivate students' ability to solve complex engineering problems. Based on OBE output orientation and CDIO engineering education concept and method, student-centered integrated training system of embedded software is constructed, aiming at cultivating professional talents with innovative consciousness and ability to solve complex engineering problems and meeting graduation requirements of engineering education certification standards.