Reviewerly/exHarmony huggingface dataset:
Inhibition of Lexical Representations after Violated Semantic Predictions

There is a consensus that humans predict upcoming words during sentence processing. Prediction makes language comprehension fast and efficient if this anticipatory processing is accurate. However, often times, predictions are not correct. There is a lack of research investigating the cognitive operations at play when predictions are violated. According to several proposals, such violations lead to an inhibition of the predicted word to facilitate the integration of the unexpected word. Across four experiments, we have tested whether predicted words are indeed inhibited when listeners encounter unexpected stimuli, and whether the linguistic status (word or sound) and semantic congruency of a word (plausible or implausible) influences this purported inhibitory process. Using a Cross-Modal Lexical Priming paradigm, we showed that when predictions are violated, the activation of the predicted word is inhibited, resulting in increased reaction times. These inhibitory effects appear to be language specific, in that they are only observed after unexpected words , as opposed to non-linguistic sounds ( tones ). However, contrary to a long-held assumption in the field of sentence processing, inhibitory effects are not modulated by the semantic congruency of the unexpected word (i.e., whether the unexpected word is plausible within the sentence context). Indeed, in the current study, any linguistic information that violated listenersâ€™ semantic prediction resulted in the inhibition of the predicted word. Thus, the current findings are more compatible with a view in which unexpected linguistic events that are meaningful engage inhibitory processes with the specific purpose of inhibiting the predicted, though out-of-date, word. Along with a rich history of literature that has shown that unexpected events evoke domain-general inhibitory processing, the current findings raise the possibility that domain-general inhibitory control is responsible for this language specific inhibition.
The Case for Negotiation Robots in simulated workplace negotiations A Theoretical Approach

Job negotiations are an anxiety-inducing and highly important form of social interaction. Most people are not sufficiently trained in negotiation strategies and often do not receive job offers that are conducive to financial stability. With the rise of virtual agents and robotics that are capable of modeling social interactions, a significant research effort has been established to create realistic simulations of negotiations. While the bulk of this research has focused on virtual agents as a medium for simulated negotiations, we propose that embodied agents can be utilized to model the inherent nuances in human interaction. In this paper, we propose a study that aims to evaluate the effectiveness of embodied agents compared to virtual agents in simulated negotiations with human participants.
Chapter 32: OpenCL Libraries

The OpenCL package itself does not come with any ready-made libraries, but there are some available. Some of the libraries are less developed than their CUDA relatives, but they do provide the basic functionality that is needed to complete the projects contained in Part VI. The analogue of LAPACK for the OpenCL platform is clMAGMA, but it is available only for the AMD graphics card platform. The device maker AMD also put their OpenCL development tools into open source and one of the products of that effort is the clFFT library that can be used for doing Fourier transforms. Finally, there is no OpenCL specific random number generation library, but the Random123 library can be effectively used in the OpenCL framework to enable individual work-items to generate random numbers in kernel functions.
Mechanism of the process of organization of computer and information technology lessons through media technologies

Organization of the teaching process of informatics and information technologies on the basis of media technologies is presented. It is impossible not to recognize that the role and possibilities of media technologies have increased several times in the current era of globalization and the informational conditions of the society. Of course, the need of the time shows that this is also important from the pedagogical point of view.
Diagnostics of the formation of students’ competencies at the university

In modern conditions, there is an acute problem of developing control and evaluation, measuring, monitoring tools that allow diagnosing the level of formation of students’ competencies at a university. The traditional assessment system cannot diagnose a student's competencies, reflecting only their knowledge component. The authors presented a methodology for diagnosing competencies based on the performance of students in the course of professional training at the university. The presented methodology, based on the competence-based paradigm, uses a qualimetric approach to assessing the professional and general cultural competencies of a student throughout the entire period of study. The article describes a cumulative system for assessing competencies, criteria, levels of formation and methods for their assessment, which allow diagnosing educational activities. This article is intended for teachers of higher education, heads of departments of the university, methodological departments, researchers involved in the diagnostics of educational activities.
Kemampuan Menyunting Teks Prosedur Kompleks Menggunakan Teknik Peer Editing Siswa Kelas X

This study aimed to determine the completeness of the ability to significantly edit complex procedural texts for class X MA Mazro'illah Lubuklinggau after the Peer Editing technique was applied. The research method is quasi-experimental. Data collection with test techniques. The data were analyzed using the T test formula. The results showed that the results of the hypothesis test were known to be 4.743. These results when consulted with tt (table with N-1 = 28-1 = 27 or db/df = 27) at a significance level of 1% that is 2.771 and a significance level of 5% is 2.052. This shows that the calculation results were greater than that at the 1% and 5% significance levels, or 4.743 &gt; 2.771 and 4.743 &gt; 2.052. The average student was greater than the KKM or 78.87 &gt; 70 and the proportion of completeness reaches 89.29%. The results of the pretest students who completed were 9 people (32.14%), while the students who did not complete were 19 people (67.86%). Then, in the post-test results, 25 students (89.29%), while those who did not complete were 3 (10.71%). In conclusion, the application of Peer Editing techniques can significantly improve the ability to edit complex procedure texts for Class X MA Mazro'illah Lubuklinggau students.&#x0D; Keywords: Editing, Peer Editing Techniques, Complex Procedure Text
Fields on the go

Bill Harvey describes two recent cases where a portable electronic fields analyser came to the rescue when gross perimetry proved inadequate
D2D Authentication Scheme for IoT-enabled Smart Home

The rapid development of Internet of things (IoT) technology has created a good technical foundation for the establishment of the smart home. However, while a smart home brings convenience to people, it also has many hidden security issues. Smart home is related to the life and property safety of users in this environment. A large number of researchers have made research on the security issues in IoT-enabled smart home systems. With the in-depth development of intelligence, the independent authentication between devices is one of the trends of smart homes in the future. Therefore, device-to-device (D2D) authentication is particularly important for smart home systems. In this paper, a D2D authentication scheme is proposed. The proposed scheme can ensure that two intelligent devices can authenticate each other with the assistance of a home gateway. The security and performance analysis shows that the proposal is secure and efficient for the application in the smart home environment.
Strategies to Optimize and Validate Tracking Performance of Single-Axis Trackers on Diffuse Sites

Tracking performance can be optimized under diffuse conditions by traveling to a flatter angle to maximize energy production of a PV power plant. Experimental results from Array Technologies' SmarTrack--TM Diffuse algorithm are presented here from a site in New York. An alternating validation strategy is described to quantify the diffuse gain over a period of roughly two months (May and June 2021). Additionally, this work includes the details of a prediction methodology used to validate the measured gains as well as estimate annual gains.
Analysis of the Inerka polygon metageosystems by means of Ensembles of machine learning models

The article describes a geoinformation algorithm for interpreting Earth remote sensing data based on the Ensemble Learning methodology. The proposed solution can be used to assess the stability of geosystems and predict natural (including exogeodynamic) processes. The difference of the created approach is determined by a fundamentally new organization scheme of the metaclassifier as a decision-making unit, as well as the use of a geosystem approach to preparing data for automated analysis using deep neural network models. The article shows that the use of ensembles, built according to the proposed method, makes it possible to carry out an operational automated analysis of spatial data for solving the problem of thematic mapping of metageosystems and natural processes. At the same time, combining models into an ensemble based on the proposed architecture of the metaclassifier makes it possible to increase the stability of the analyzing system: the accuracy of decisions made by the ensemble tends to tend to the accuracy of the most efficient monoclassifier of the system. The integration of individual classifiers into ensembles makes it possible to approach the solution of the scientific problem of finding classifier hyperparameters through the combined use of models of the same type with different configurations. The formation of a metaclassifier according to the proposed algorithm is an opportunity to add an element of predictability and control to the use of neural network models, which are traditionally a “black box”. Mapping of the geosystems of the Inerka test site shows their weak resistance to recreational development. The main limiting factors are the composition of Quaternary deposits, the nature of the relief, the mechanical composition of soils, soil moisture, the thickness of the humus horizon of the soil, the genesis and composition of vegetation.
Conceptual exploration and comparative study on the use of deep learning approach in HAR models

Human Activity Recognition (HAR) has taken great attention from researchers last few years, because of the promising results shown by deep learning, and the necessity to make a recognizer system, in this paper a comparison between two types of Convolutional Neural Network (CNN) architectures will be presented. Two Dimensional (2D) CNN followed by a Recurrent Neural Network (RNN) referring to it as 2D-CNN-RNN, and 3D-CNN. Filter with 3D-CNN will be used, after training and testing the models with two different datasets, KTH which has six human activities (Boxing, Handclapping, Handwaving, Walking, Jogging, and Running), and UT-Interaction dataset that has six interaction activities (Handshake, Hug, Kick, Point, Punch, and Push). 3D-CNN shown remarkable results with the aid of filter, but without filter, the dominant was 2D-CNN-RNN models.
Neural and cognitive mechanisms for vocal communication

Vocal communication is a central feature of social behavior across numerous species. While the neural systems underlying vocalization in humans and animals is well described, less is known about how these circuits enable naturalistic vocal interactions. To investigate how the human brain gives rise to ethologically relevant vocal interactions—conversational turn-taking—a series of intracranial recording and perturbation experiments are performed to precisely assay neural activity while neurosurgical patients engage in both task-based and unconstrained turn-taking. In these social contexts, spatially and functionally distinct networks are uncovered, which are critical for a speaker’s ability to comprehend their partner’s turns, plan their own turns, and articulate the speech comprising those turns. To better understand the neural mechanisms underlying specific computations relevant to vocal communication, a theoretical framework is constructed, which consists of the cognitive modules required for generating communicative action during interaction (e.g., vocalization, co-speech gesture). This model is designed to account for the behavioral and neurobiological features of both naturalistic human language and animal communication; therefore, this species-general framework is intended to facilitate the identification of cognitive analogues between human and non-human interaction—which may rely on similar neural mechanisms. [Work supported by the NIH &amp; Simons Collaboration on the Global Brain.]
THE PEDAGOGICAL CONDITIONS OF PREPARATION OF THE FUTURE CHEMISTRY TEACHER FOR THE FORMATION OF GNOTIC SKILLS AT STUDENTS IN EXTRACURRICULAR ACTIVITIES

The article identifies the features of preparing for the future chemistry teacher in the context of educational reforms. The content of the latter research and publications is analyzed. The method of factor analysis was used, the expert groupwas interviewed and four typical groups were identified, the main characteristic of which was the average value of the factor.&#x0D; The leading pedagogical conditions of preparation of the future chemistry teacher for the formation of gnostic skills at students in extracurricular activities are defined and characterized, (creation of a motivational basis to the realization of extracurricular activity in Chemistry in the general secondary education institutions; acquisition of the initial professional experience during the organization of training in higher education institutions, arming of modern forms and methods of extracurricular activities in Chemistry, focused on the formation of gnostic skills in students; creating a developmental educational environment for higher education institutions to actively involve students in cognitive and research activities; the use of modern innovative pedagogical technologies in training future Chemistry teacher; building an individual trajectory of students' professional preparation of highereducation on the purpose of the organization of extracurricular activities in the general secondary education institutions), the effectiveness of their implementation in the educational process is substantiated. On the basis of the Professional Standard"Teacher of General Secondary Education" the importance of using innovative technologies in Chemistry is determined. It is proved that the outlined pedagogical conditions are the leading factors that provide effective mastering of knowledge inchemistry by applicants for higher education and the possibility of their introduction into the educational process of general secondary education institutions to implement professional tasks, successfully organize extracurricular activities, create positive motivation to learn, understand life priorities, ensuring the holistic development of a personality capable of self-development, self-improvement and becoming a future professional in his field.
Learning Energy-Based Models with Adversarial Training

We study a new approach to learning energy-based models (EBMs) based on adversarial training (AT). We show that (binary) AT learns a special kind of energy function that models the support of the data distribution, and the learning process is closely related to MCMC-based maximum likelihood learning of EBMs. We further propose improved techniques for generative modeling with AT, and demonstrate that this new approach is capable of generating diverse and realistic images. Aside from having competitive image generation performance to explicit EBMs, the studied approach is stable to train, is well-suited for image translation tasks, and exhibits strong out-of-distribution adversarial robustness. Our results demonstrate the viability of the AT approach to generative modeling, suggesting that AT is a competitive alternative approach to learning EBMs.
PENINGKATAN HASIL BELAJAR PKN MATERI PEMILU DAN PILKADA MELALUI MODEL PEMBELAJARAN KOOPERATIF TIPE STUDENT TEAM ACHIEVEMENT DIVISION

The purpose of this study is to improve teacher performance, student learning activities, and student learning outcomes in electoral and election material by applying the STAD type cooperative learning model. This research is a classroom action research conducted in two cycles. Each cycle consists of two meetings and through four stages, namely planning, implementing actions, observing, and reflecting. The subjects in this study were the sixth grade students of Karngbinangun State Elementary School, Lamongan District, 2017/2018 school year, with 15 students consisting of 11 male students and 4 female students. Data collection techniques used are test and non-test techniques. Data analysis was carried out by analyzing qualitative and quantitative data. Based on the implementation of the first cycle the value of teacher performance is 83.08 (AB). In the second cycle, the teacher's performance score increased to 89.17 (A). Student learning activities reached 65.12% and in the second cycle increased to 79.87%. In the first cycle, the average value of student learning outcomes reached 70.67 with a complete percentage of classical learning of 66.67%. Meanwhile, in the second cycle the average value of student learning outcomes increased to 81.67 with a complete percentage of classical learning at 93.33%.
Designing an expert system to advise the IT students' Master's degree for course selection

In the university educational system, students, depending on their different conditions, need guidance to choose the best courses and the best curriculum during a semester. Lack of sufficient information about class hours, exam interactions, prerequisites for each course, variety of instructors and other conditions may lead to a wrong choice and confusion of students. In this research, an expert system is introduced that aims to guide a master student in Information Technology Management during course selection. This expert system, which is written in MATLAB software, by receiving the necessary information about the student's academic conditions and the courses passed and taking advantage of the expert's opinion, completes the database of IF-THEN Rules and allows the student to choose suitable courses. As a human expert, the system provides intellectual assistance. The proposed system was evaluated using Mamdani's fuzzy inference method and determining several design indicators, and then its accuracy was evaluated with experimental data, and the obtained results indicated that the system was desirable.
The SiTa Trilingual Translation System

The National Languages Processing Center (NLPC), at the University of Moratuwa has been developing the SiTa Computer-Assisted Translation System since 2018.
Reflections on Sound Associations and Sonic Digital Environments

This essay uses a “thought experiment” in order to combine theories of perception with sound practices. For that, it explores the concept of “object of thought” and the process of brain-associations in relation to acousmatic composition and reduced listening. Throughout the hypothetical premise of a falling tree, the study brings to discussion digital environments, in particular in relation to methodologies behind game engines. Eventually, it proposes to divide the question “If a tree falls in a forest and no one is around to hear it, does it make a sound?” according to its multiple angles—the falling tree, the tree of thought, the sound of the fall, and the tree in the digital environment—in order to arrive at the ultimate question: Is there a tree, did it fall, is there a forest, is there a sound?
Demographic and Perception Studies of a Mobile Application among Dog Breeders and Owners

Information and Communication Technology is, today, an integral part of our daily world. However, despite the wide use of this technology elsewhere, it has only recently been adopted for engagement in veterinary services, especially in India. It was in this context that an application for dog breeders and owners was developed, and their perceptions about various aspects of the application were assessed, as well as the possible use and impact that veterinary applications could have in improving veterinarian client management. The present investigation was exploratory in nature and conducted with dog breeders and owners from four districts of Kerala. After due consultation with prominent veterinarians and scientists, prioritisation of the contents was followed. The contents were vetted, compiled, and the data was fed to a native mobile application. A sample (n = 40) of dog breeders/owners was chosen from the four districts. Along with telephonic follow-ups, APK (Android Package) and Google form questionnaires were mailed to the dog owners/ breeders. The breeders/owners were mostly young, educated males who had access to and were comfortable using a smartphone. The 'VetCan' mobile application was mainly reported to have an average engagement, was highly functional, possessed pleasant aesthetics, and contained highly informational content.
CONCEPTUAL APPROACH TO THE DEVELOPMENT OF PEDAGOGICAL SKILLS OF TEACHERS OF AN OIL TECHNICAL SCHOOL

The article provides a brief analysis of research on the problems of developing the pedagogical skills of Russian teachers. This problem was paid attention to by many coryphaeus of Russian pedagogy of the ХХ century, whose works continue to be relevant to this day. Number of foreign researchers pay attention to the teachers’ profes­ sional qualities. Based on the comprehension of these works, the author presents the concept of the development of teachers’ pedagogical skills who work in vocational education organization of a technical profile. In the Petroleum College, which the author manages, in addition to professional teachers with pedagogical education, there are also teachers without pedagogical education, also industry workers from the petroleum field. Thus, the teaching staff is a multi­layered conglomerate that requires specific work to develop the components of pedagogical skills among all members of the team. The characteristics of these components are presented in this article.
Evaluation of a distributed deep learning framework as a reference architecture for a cloud environment

Distributed deep learning is becoming increasingly important due to the size of deep neural networks. The sheer volume of the input datasets used in the process can have a significant negative effect on the training time of the model. As a consequence of physical limitations, the resources of a single node cannot be scaled to a sufficient level for efficient training. As such, different parallel and distributed solutions exist in order to solve this problem. In this paper, we measured the scalability of Horovod, a distributed deep learning framework (available as a reference architecture) with different parameters on the research infrastructure called ELKH Cloud. The experiment was conducted in order to verify the scalability of the framework on the general purpose infrastructure, which was not designed primarily for distributed deep learning applications. Measurements assessing model accuracy were also performed, for the purpose of validating the distributed training process.