Reviewerly/exHarmony huggingface dataset:
STRUCTURES IN THE HUMAN BRAIN THAT RECOGNIZE THE MEANING OF WORDS

The emergence of artificial systems that communicate by voice makes it necessary to study more closely the speech and human ability to quickly understand the meaning of words. Our experiments show that in groups of words related in their meaning a person recognizes some words faster and others more slowly. Words concatenate in linear chains, and we believe that this reflects the arrangement of word storage system in the cerebral cortex. An analysis of all adjectives of the Russian language (with their translations into English) showed that they can be arranged into a densely packed system consisting of three sectors for words with positive, neutral and negative emotional content. The sectors contain groups of words that are close in meaning. The chains of words fill the area with a system of radial rays. We intend to spot experimentally these structures in the human brain.
USO DA TELEMEDICINA AO LONGO DE SEU DESENVOLVIMENTO: REVISÃO DE LITERATURA

A recent discussion arose in Brazilian law with the creation of the COVID-19 vaccine, in which there was a collision of fundamental norms, on the one hand the collective interest in integral immunization and mitigation of the effects of the disease and on the other, the freedom of conscience of parents who refuse to vaccinate their children for reasons of philosophical conviction.Then, the problem reached the Federal Supreme Court in a regime of general repercussion in RE 1.267.879/SP,establishing the thesis of the illegitimacy of parents to vaccinate their children for philosophical reasons, considering that there is a prevalence of the interest of the community .Furthermore, the present study will unfold from the perspective of the doctrines of John Stuart Mill and Robert Nozick, verifying whether the Supreme Court's decision conforms to the thinking of these authors.In short, the aim is to promote collective well-being and completely dissipate COVID-19.
Color-wall: Adaptive Color Filter to Reduce Digital Distractions during PC Work

As the Attention Economy has grown, numerous digital contents are made with the intention of capturing users’ attention and spending more of their time by the use of attractive graphics and color psychology. In this paper, we propose a novel defense strategy, called a color-wall, to block digital distraction brought on by the consumption of visually seductive and addictive digital content. When it detects that a user is viewing media or using applications unrelated to the main task, it removes colors from the screen (gray-scaling) to make them less aesthetically pleasing and directs the user away from looking at them. We implemented a mac OS software as a proof-of-concept for the color-wall and conducted user testing (N=14) to assess the effectiveness of the proposed strategy. The evaluation results suggest that the color-wall is an effective strategy for reducing unwanted digital distractions such as browsing restricted content (YouTube, Twitter, etc.) while working on a PC.
The Abstract Book of the XX Conference for Junior Scientists in Psychology

Conference for Junior Scientists in Psychology is an annual event organized by Ph.D. students at Vilnius University, Institute of Psychology. The conference gives an opportunity for psychology students and junior researchers from various universities in Lithuania to present their scientific work and findings. In 2023, the conference focused on the importance of community and collaboration in research work.
Relation Extraction for Knowledge Graph Generation in the Agriculture Domain: A Case Study on Soybean Pests and Disease

Highlights With the aim to reduce the burden of acquiring expert knowledge and strengthen the connection between written knowledge and the fields, this article investigated the problem of automatically extracting and organizing soybean pests and disease knowledge from text. Entities and relations were extracted using multiple models with deep neural network structures. Performance of these models were compared and evaluated in detail. A knowledge graph was automatically constructed using the extracted information, and made publicly available. ABSTRACT. Precision agriculture is an emerging type of agriculture that intensively uses information technology to automate agricultural production. Soybean (Glycine max (L.) Merri.), is an important crop in China, with an annual demand of approximately 110 million tons. However, in China, soybean production is threatened by more than 30 kinds of disease and 100 kinds of pests. With the rapidly increasing specialized information in the literature, it is difficult for farmers to keep up. Relation extraction automatically identifies and extracts structured knowledge from natural language text and thus can help to alleviate the problem. In this study, we propose to employ relation extraction to systematically extract information from expert-written text, and generate a knowledge graph from the extracted information. This case study was planned in China, therefore we mainly used Chinese texts. Firstly, we carefully chose expert-written text on soybean pests and disease, labeled the entities, and classified their thematic relations into five categories. Then, we built and trained three relation extraction models using state-of-the-art deep learning architectures and evaluated their performance on our task. Finally, we constructed an example knowledge graph from the extracted information and demonstrated their potential usage for automatic reasoning and solution recommendation for pests and disease prevention. In total, this study sampled 1038 entities and 1569 relation instances. Experimental results showed that our best model achieved an F1 score of 98.49% on identifying relations from text. Experimental results also showed the effectiveness of the example knowledge graph. Keywords: Bidirectional encoder representation from transformers, Knowledge graph, Relation extraction, Soybean pests and disease.
Experimental 61-partite entanglement on a three-dimensional photonic chip

Multipartite entanglements are essential resources for proceeding tasks in quantum information science and technology. However, generating and verifying them present significant challenges, such as the stringent requirements for manipulations and the need for a huge number of building-blocks as the systems scale up. Here, we propose and experimentally demonstrate the heralded multipartite entanglements on a three-dimensional photonic chip. Integrated photonics provide a physically scalable way to achieve an extensive and adjustable architecture. Through sophisticated Hamiltonian engineering, we are able to control the coherent evolution of shared single photon in the multiple spatial modes, dynamically tuning the induced high-order W-states of different orders in a single photonic chip. Using an effective witness, we successfully observe and verify 61-partite quantum entanglements in a 121-site photonic lattice. Our results, together with the single-site-addressable platform, offer new insights into the accessible size of quantum entanglements and may facilitate the developments of large-scale quantum information processing applications.
Automated WebAssembly Function Purpose Identification With Semantics-Aware Analysis

WebAssembly is a recent web standard built for better performance in web applications. The standard defines a binary code format to use as a compilation target for a variety of languages, such as C, C++, and Rust. The standard also defines a text representation for readability, although, WebAssembly modules are difficult to interpret by human readers, regardless of their experience level. This makes it difficult to understand and maintain any existing WebAssembly code. As a result, third-party WebAssembly modules need to be implicitly trusted by developers as verifying the functionality themselves may not be feasible.
Utilizing a projection neural network to convex quadratic multi‐objective programming problems

Summary In this paper, we propose a projection neural network model for solving convex quadratic multi‐objective optimization problem (CQMOP). The CQMOP is first converted into an equivalent convex nonlinear programming problem by the means of the weighted sum method, where the Pareto optimal solutions are calculated via different values of weights. A neural network model is then constructed for solving the obtained convex problem. It is shown that the presented neural network is stable in the sense of Lyapunov and is globally convergent. Simulation results are given to illustrate the global convergence and performance of the suggested model. Both theoretical and numerical approaches are studied. Numerical results are in good agreement with the proved theoretical concepts.
Applications of Augmented Reality to Provide Quality Education: A Survey

Abstract: Traditional methods of learning such as reading books and copying texts is becoming a thing of the past. Everything is becoming increasingly digitized and is being driven by technology innovations. Bringing new learning formats based on technology in the classrooms can lead to increased student engagement which in turn will make the knowledge and skills stay longer. Thus, adapting technological solutions to education is very important. Augmented Reality (AR) is an enhanced version of the real world which is achieved using digital visual elements, audio and other sensory stimuli. This is a growing technology. Since it provides many powerful visualizations, AR can be used as a powerful learning tool. This paper will provide an overview of AR and the hardware required for AR application and some of the AR techniques required to successfully overlay virtual contents over the real-world objects. Further, it explains the importance of AR in education and evaluate the impact of AR in education through various works
Automatic Identification and Extraction of Assumptions on GitHub

In software development, due to the lack of knowledge or information, time pressure, complex context, and many other factors, various uncertainties emerge during the development process, leading to assumptions scattered in projects.Being unaware of certain assumptions can result in critical problems (e.g., system vulnerability and failures).The prerequisite of analyzing and understanding assumptions in software development is to identify and extract those assumptions with acceptable effort.In this paper, we proposed a tool (i.e., Assumption Miner) to automatically identify and extract assumptions on GitHub projects.To evaluate the applicability of Assumption Miner, we first presented an example of using the tool to mine assumptions from one large and popular deep learning framework project: the TensorFlow project on GitHub.We then conducted an evaluation of the tool.The results show that Assumption Miner can effectively identify and extract assumptions from the repositories on GitHub.
A Sampling-based Next-Best-View Path Planner for Environment Exploration

A new path planner to explore the surrounding environment algorithm is presented for the aerial robot. This algorithm combines Next-Best-View (NBV) sampling and frontier exploration together to find unknown large areas. We first compute the nearby area, namely the frontier area, which can guide the exploration direction for the robot roughly, then a node tree representing the NBV of the robot is generated for the robot to follow. Next, a continuous trajectory-generated method is proposed where a B-spline curve representing the robot trajectory can follow these selected viewpoints in the history tree. We evaluate the effect of our algorithm in a simulated environment.
FAIR Data by Design: A Case of the DiVA Portal

FAIR Data Principles is a guideline for making data and other digital objects findable, accessible, interoperable, and reusable.Thus far, the traction and uptake of the principle are primarily in the domain of bio and natural sciences.The knowledge gap is the application of the FAIR Data Principles in designing data repositories for FAIR data in the academic data ecosystem.This paper provides a critical insight into how the principle can be utilised as a paradigm to design data that embodies the tenets of FAIR Data Principles.We conducted a case study of the DiVA portal, an information repository and finding tool in Sweden, to explicate FAIR data by design.The portal scored high in a qualitative assessment against the 15 facets of FAIR Data Principles, as illustrated by the high density of green cells in the traffic light rating matrix (see Table 1).It indicates the robustness of data in the portal that is easy to share, find, and reuse.This study suggests practitioners operationalise FAIR Data Principles in their data repositories by design through systems and policies underpinned by the principle.It would enrich data governance and management for the back office and data experiences for end users.The study also advances the knowledge base on data management through a granular exposition of FAIR data by design.
Assessing The Interference of Mother Tongue Towards Students’ Spoken English Ability at SMPN 39 SBT

This research was conducted through descriptive qualitative research with the aim of the study are to find out kinds of phonological interference in the spoken English by students at SMPN 39 SBT and to describe factors which affecting the phonological interference in the spoken English by students at SMPN 39 SBT. The study taken a place in SMPN 39 SBT which located in desa Mida, Kec. Pulau Gorom. The subject of this study were eleven students of second grade at SMPN 39 SBT which spoken Bahasa Gorom as their mother tongue. The data were collected by using video recording, field not and interview. The researcher uses the content analysis which focuses on analyzing kinds of phonological interference by Uriel Weinrich, and the factors which affecting the phonological interference Rod Ellis. The result shown that there are 4 kinds of phonological interference found in the students’ utterances. Those are; 1). Under-differentiation of Phonemes. 2). Over-differentiation of Phonemes. 3). Reinterpretation of Distinction. 4). Actual Phone Substitution. The factors which include internal and external factors found in this study. They are; a). Motivation. b). Language Learners’ Attitude. c). Learners’ Personality. d). Teacher’s Behavior. e). Learning Environment.
Using Crushed Glass with Sand as a Single and Dual Filter Media for Removal of Turbidity from Drinking Water

The aim of this research is trying to find that environmentally and economically efficient way for reuse industrial solid wastes of glass as an alternative filter media to sand to remove turbidity from drinking water.It is required to set a pilot filtration unit which included mainly three transparent columns.It was used to remove the turbidity of synthetic turbid water that consisted of three filter media.The first and second filters represent single media filters of glass and sand, respectively.The third filter represents a filter of dual media of sand at the bottom layer and glass at the top layer.The single media of glass filter and the dual media of glass-sand filter have a maximum removal efficiency of water turbidity in comparison with the single media of sand filter.The maximum removal efficiencies of glass filter, glass-sand filter, and sand filter are 94% and 95%, and 87%, respectively, at influent turbidity of 25 NTU and a filtration rate of 5 m/h.Statistical analysis using stepwise multiple linear regression models had been carried out by utilizing (DataFit, version 9. 1. 32) program models give a good matching between the measured and the predicted values for simulated drinking water for sand, glass, and glass-sand media with the determination coefficient (R² ) equal to 1.
The terminological tagging of the NooJ italian compound word dictionary

In this paper, and in relation to the construction of electronic dictionaries for NooJ, we will deal with the tagging of Italian compound words, and with how it differs from that of simple words as for methods, functions, and purposes. We will especially focus our attention on the tagging of technical-scientific compound words, demonstrating how this operation, in NooJ, represents a crucial tool for both information extraction and knowledge automatic management and representation. Furthermore, with the intention to producing a complete analysis, we will provide the definitions of simple word and compound word, from both a formal and a linguistic point of view. As for the linguistic examination, we will adopt two different approaches. For the first one, we will use the analytic methods of Zellig S. Harris, who first set out, in structuralist terms and in relation to English, the study of the composition of different morphemes in more complex linguistic units, hence also of word groups or phrases. For the second one, we will make extensive reference to the methodological framework of language formalization described by Maurice Gross' Lexicon-Grammar, as to its subsequent adaptations to the Italian language. Finally, as we will see, it will be of fundamental importance for us to differentiate the definitions that we will give here of compound words from the more generic and less precise one of multiword expressions (MWE). To justify this differentiation, we will provide not only formal indications, but also lexical, morphosyntactic and semantic ones.
Edutainment Content Production Platform Based on Activity Control Using Skeleton Tracking

During the COVID-19 pandemic, the activities required for child physical development were reduced because classes were conducted remotely.Thus, an interactive edutainment content that can assist the physical and cognitive development of children in indoor environments is required.In this study, we designed an edutainment content production platform (ECPP) that allows teachers to design and produce an educational content using students' movements.Teachers can develop an educational content by analyzing and modifying the children's response to the designed edutainment content.The skeleton tracking of the human body using a depth sensor was used for the user interface and activity analysis.The proposed platform allows teachers to set images and movements for educational icons, as well as visual and sound effects that occur when a child touches the icons.The ECPP includes an activity control function that allows teachers to analyze the amounts of activity and movement, and then adjust the movement level in the edutainment content.In addition, a content management module allows teachers to store and share an interactive content.
Resúmenes al Español

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Resúmenes al Español. Am J Intellect Dev Disabil 1 May 2023; 128 (3): 271–272. doi: https://doi.org/10.1352/1944-7558-128.3.271 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search
Résumés en Français

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Résumés en Français. Am J Intellect Dev Disabil 1 May 2023; 128 (3): 269–270. doi: https://doi.org/10.1352/1944-7558-128.3.269 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search
Computing Process-Specific Constraints

This squib demonstrates how process-specific constraints—in which related but distinct processes in a language can be subject to differing conditions—can be captured with Boolean monadic recursive schemes (BMRSs), a computational formalism for phonological analysis based in mathematical logic. We use the case study of pharyngeal harmony in Palestinian Arabic, which motivated a discussion between Davis (1995) and McCarthy (1997) about the relative advantages and drawbacks of rule-based and Optimality Theory frameworks. We show how BMRS grammars naturally capture process-specific constraints in a way comparable to OT, while still being more computationally restrictive.
Online intrusion detection mechanism based on model migration in intelligent pumped storage power stations

With the continuous integration of new energy into the power grid, various new attacks continue to emerge and the feature distributions are constantly changing during the deployment of intelligent pumped storage power stations. The intrusion detection model trained on the old data is hard to effectively identify new attacks, and it is difficult to update the intrusion detection model in time when lacking data. To solve this issue, by using model-based transfer learning methods, in this paper we propose a convolutional neural network (CNN) based transfer online sequential extreme learning machine (TOS-ELM) scheme to enable the online intrusion detection, which is called CNN-TOSELM in this paper. In our proposed scheme, we use pre-trained CNN to extract the characteristics of the target domain data as input, and then build online learning classifier TOS-ELM to transfer the parameter of the ELM classifier of the source domain. Experimental results show the proposed CNNTOSELM scheme can achieve better detection performance and extremely short model update time for intelligent pumped storage power stations.
A counterfactual analysis of adnominal modifiers

In this article, I shall argue for a counterfactual analysis of the semantics of some ad-nominal modifiers. This analysis formalizes the intuition that adnominal modifiers are always restrictive in some sense. Technically, the proposal is formalized with an opera-tor that applies to two intensional entities of type &lt;s,et&gt; and returns as the value the same type of semantic entity (type: &lt;s,et&gt;). In terms of how the rule works, it resem-bles Predicate Modification since it requires a special rule. However, it does not inter-sect the two sets in question. Rather, the rule yields a set of entities that are not neces-sarily a subset of the entities specified by the common noun in the actual world. I call this semantic procedure Restrictive Modification (RM). Essential reasoning is given as follows: the property of being x that has the modifier property and if in all closest worlds w in which x had a crucial property that all CN entities have, then x would have the CN property in w. For example, in the case of stone lion, it denotes the prop-erty of being x made of stone such that if x were to possess a crucial property that a re-al lion has (say, the property of being alive with flesh and blood), then x would be a real lion. This reasoning applies to a variety of adjective types. Some problematic ex-amples such as house key and ice water remain, and they are a reserved for a future study.
Embedded Encryption and Compression Solution for Resource-Constrained ARM Microcontrollers

This paper investigates compression and encryption algorithms for use in resource-constrained systems. The investigation is structured around a suitable solution for lightweight, fixed-point, resource-constrained microcontrollers, specifically the STM32F0. During the early development stages, simulation testing using sample data allowed for system validation. Hardware-based testing using live and sample data allowed optimisation and validation of the system for use on the STM32F0. The developed system uses RSA encryption and LZSS compression as a solution to data encryption and compression on resource-constrained microcontrollers. The project’s code is available on GitHub.