Reviewerly/exHarmony huggingface dataset:
Exploring the Possibility of a Recovery of Physics Process Properties from a Neural Network Model

The application of machine learning methods to particle physics often does not provide enough understanding of the underlying physics. An interpretable model which provides a way to improve our knowledge of the mechanism governing a physical system directly from the data can be very useful. In this paper, we introduce a simple artificial physical generator based on the Quantum chromodynamical (QCD) fragmentation process. The data simulated from the generator are then passed to a neural network model which we base only on the partial knowledge of the generator. We aimed to see if the interpretation of the generated data can provide the probability distributions of basic processes of such a physical system. This way, some of the information we omitted from the network model on purpose is recovered. We believe this approach can be beneficial in the analysis of real QCD processes.
Grammatical Error Found in the Academic Essays Written by Students of English Education

Writing academically demands students to use correct grammar yet students still make error grammatically. This research reports on grammatical errors in academic essays written by Students of English Education. This study addresses two research questions; 1) What are the grammatical errors made by Students of the English Education Program? 2) From the error classification, what is the major error made? The method used is a qualitative method. The sample subjects were 5 of 15 students writing the essays. They are fifth semester students from English Education study program, Artha Wacana Christian University, Kupang. The samples were determined by purposive sampling. Data was collected using documentation techniques. The results indicated that students have made the grammatical errors in their academic essays. The errors committed by the students are; 1) noun-noun groups, this part consists of four categories, students made error in all categories; 2) Verb-verb groups, this part has nine categories; students committed errors in three categories; 3) Preposition error, this part has three categories. Students made errors in two categories; 4) Sentence structure; this part consists of eight categories. Students made errors in three categories. The major errors committed by the students are; first, in noun-noun groups by using inappropriate combination of subject and verb agreementand omitting the plural marker –s; second, in verb-verb groups in which the errors are mainly in the omission of suffix –s, -es, -ed and the omission of auxiliary verbs. Thus, students of English education need to improve their writing on academic essays.
Human factors for the evaluation of the user expertise in the usage of power tools

In order to optimize the use of hand/ power tools, user differences such as the influence of user expertise must be considered in product design.Therefore, product-independent non-applicationspecific variables are needed to objectively capture user expertise.In sports science, the characteristics of movement are used to evaluate the training level.To what extent these variables can be used for product development is unknown.Therefore, a study with 6 male subjects was carried out to analyze correlations between efficiency and characteristics in the movement behavior of the subjects when hammering.Results indicate a clear difference between experienced and less experienced users.Moreover, the movement of the more efficient subjects was spreading less than those of the less efficient ones.
The Influence of Picture Book to the Storytelling skill of Preschool Children

The benefit of storytelling activity to children’s skill development is to provide a positive contribution to children’s language skill. This research aimed to determine the impact of the picture book to the storytelling skill of children aged 4-5 years. The research subjects consisted of two kindergartens in Yogyakarta (Pringwulung and Cempaka kindergarten) Indonesia. The participants are 40 children. The data were used quasi-experimental research design. The research data obtained were analyzed with t-test through SPSS 16 program to see the differences between the experimental group and the control group. The result of this research was a significant influence of using picture book on the storytelling skill of preschool children. The recommendation from the result of this research was provided to parents and teachers particularly to develop children’s communication skill and practitioner in the discussion that especially emphasized addressing the need to increase opportunities for storytelling skill of preschool children in good stimulation.
English Vocabulary Development of Non-Linguistic Specialties Students using Mobile Application

The research findings indicate that most students are aware of the importance of systematic lexis learning, yet, the problem of students’ poor vocabulary remains. Mobile application is a powerful and beneficial educational tool that can be efficiently used both by teachers and students. However, the issue of FL vocabulary development via mobile applications has received little attention in Ukraine, especially in the context of the university students’ perception. Furthermore, there is no well-balanced vocabulary program in most Ukrainian universities. This paper, first of all, outlines the key points of the constructivist pedagogy and overviews literature regarding the use of technology in FL vocabulary teaching. It further describes the results of a survey conducted among Bachelor students of non-linguistic specialties regarding their interests and problems in learning FL. The research among students revealed that the main problems in learning FL concern mastering new vocabulary, speaking and listening. The authors attempt to refer the existing problems to students’ abilities to remember words and their inability to recall known words. The article summarizes the following advantages of using “Vocabulary for International English Language Testing Service (IELTS)” mobile application through the students’ perspective verified via teacher’s evaluation: free access, ease to use, tailored to individual needs and style of learning, availability of useful spoken vocabulary and sound recordings. Some suggestions concerning possible improvements of the mobile application have been provided as well. The findings of the paper call for incorporation of technological tools in FL vocabulary teaching.
Detailing explanations in the recommender system based on matching temporal knowledge

The problem of matching knowledge in the temporal aspect when constructing explanations for recommendations is considered. Matching allows reducing the influence of conflicting knowledge on the explanation in a recommender system.A model of knowledge representation in the form of a temporal rule with the explanation constraint is proposed. The temporal rule sets the order for two sets of events of the same type that occurred at two different time intervals in time. An explanation constraint establishes a correspondence between the temporal order represented by the rule for a pair of intervals and the description of temporal dynamics for a given time period. This dynamic is represented by the explanation of the recommendation. The model is designed to match knowledge, taking into account the explanation constraint, as well as further use the matched knowledge to clarify explanations based on the results of the intelligent system.A method for clarifying explanations in a recommender system based on knowledge matching in the form of temporal rules is developed. The method uses records of purchases of goods, services or their ratings as input data. The method identifies a subset of rules matched in the temporal aspect, which represent the same dynamics of consumer demand for the target item (increase or decrease) as explanations in the recommender system. Matching of temporal knowledge makes it possible to form a refined list of explanations. This list includes basic and clarifying explanations. The basic explanation reflects the dynamics of user interests for the entire given period of time. Clarifying explanation specifies changes in demand for individual intervals within a given time period. The use of the temporal dynamics of user preferences in the explanation is aimed at increasing confidence in the received recommendations
A robust watermarking algorithm for medical images

&lt;p&gt;Integrated healthcare systems require the transmission of medical images between medical centres. The presence of watermarks in such images has become important for patient privacy protection. However, some important issues should be considered while watermarking an image. Among these issues, the watermark should be robust against attacks and does not affect the quality of the image. In this paper, a watermarking approach employing a robust dynamic secret code is proposed. This approach is to process every pixel of the digital image and not only the pixels of the regions of non-interest at the same time it preserves the image details. The performance of the proposed approach is evaluated using several performance measures such as the Mean Square Error (MSE), the Mean Absolute Error (MAE), the Peak Signal to Noise Ratio (PSNR), the Universal Image Quality Index (UIQI) and the Structural Similarity Index (SSIM). The proposed approach has been tested and shown robustness in detecting the intentional attacks that change image, specifically the most important diagnostic information.&lt;/p&gt;
Classification of optimal quaternary Hermitian LCD codes of dimension $2$

Hermitian linear complementary dual codes are linear codes whose intersections with their Hermitian dual codes are trivial.&#x0D; The largest minimum weight among quaternary Hermitian linear complementary dual codes of dimension $2$ is known for each length. We give the complete classification of optimal quaternary Hermitian linear complementary dual codes of dimension $2$. Hermitian linear complementary dual codes are linear codes whose intersections with their Hermitian dual codes are trivial.&#x0D; The largest minimum weight among quaternary Hermitian linear complementary dual codes of dimension $2$ is known for each length. We give the complete classification of optimal quaternary Hermitian linear complementary dual codes of dimension $2$.
Semantic frames and semantic networks in the Health Science Corpus

The aim of this paper is to apply frame semantics principles to the analysis of a specialized corpus, the Health Science Corpus, implemented in the lexical database SciE-Lex. Taking FrameNet as the basis for this research, I will assign frame semantic features to Scie-Lex data in order to highlight the shared semantic and syntactic background of the related words in the biomedical register, give motivation to their patterns of collocates and establish frame-based semantic networks of related lexical units.
Scientific Approaches to Postmodern Spirituality: Theoretical and Methodological Aspects

Today spirituality in the educational process as an independent object of formation and study is practically absent. About this concept is only a unsystematic mention within secondary topics. However, without certainty regarding this concept and the concentration of the educational process on it, it is impossible to solve the key tasks of educational activity. Without the ideas of spirituality and spiritual values formed in the personality, it is impossible to talk about the presence of the spiritual foundations of development and life. The culture of spirituality in the modern world is quite similar to that in the 20th century, because today society provokes a spontaneous acceleration of the pace of changes in life, and therefore the perception of the surrounding world and events in it also changes: knowledge and values become unstable ephemeral. Post-industrial society focuses on material successes, ignoring utilitarian values, and sceptical attitude towards reality often develops into nihilism. The world in which we live gradually begins to resemble chaos, in which there are no moral guidelines and main human values, therefore, losing the real foundation in the outside world, a person often turns to the inner world, to spirituality, in order to hide from “world” problems and difficulties.
Sense identification data: A dataset for lexical semantics

Sense Identification is a newly proposed task; in considering a pair of terms to assess their conceptual similarity, human raters are postulated to preliminarily select a sense pair. Senses involved in this pair are those actually subject to similarity rating. The sense identification task is searching for the sense selected during the similarity rating. The sense individuation task is important to investigate strategies and sense inventories underlying human lexical access and, moreover, it is a relevant complement to the semantic similarity task. Individuating which senses are involved in the similarity rating is also crucial in order to fully assess those ratings: if we have no idea of which two senses were retrieved, on which base can we assess the score expressing their semantic proximity? The Sense Identification Dataset (SID) dataset has been built to provide a common experimental ground to systems and approaches dealing with the sense identification task. It is the first dataset specifically designed for experimenting on the mentioned task. The SID dataset was created by manually annotating with sense identifiers the term pairs from an existing dataset, the SemEval-2017 Task 2 English dataset. The original dataset was originally conceived for experimenting on the semantic similarity task, and it contains a score expressing the human similarity rating for each term pair. For each such term pair we added a pair of annotated senses: in particular, senses were annotated such that they are compatible (explicative of) with the existing similarity ratings. The SID dataset contains BabelNet sense identifiers. This sense inventory is a broadly adopted ‘naming convention’ for word senses, and such identifiers can be easily mapped onto further resources such as WordNet and WikiData, thereby enabling further processing tasks and usages in the Natural Language Processing pipeline.
Metode Wavelet-MFCC dan Korelasi dalam Pengenalan Suara Digit

Voice is the sound emitted from living things. With the development of Automatic Speech Recognition (ASR) technology, voice can be used to make it easier for humans to do something. In the ASR extraction process the features have an important role in the recognition process. The feature extraction methods that are commonly applied to ASR are MFCC and Wavelet. Each of them has advantages and disadvantages. Therefore, this study will combine the wavelet feature extraction method and MFCC to maximize the existing advantages. The proposed method is called Wavelet-MFCC. Voice recognition method that does not use recommendations. Determination of system performance using the Word Recoginition Rate (WRR) method which is validated with the K-Fold Cross Validation with the number of folds is 5. The research dataset used is voice recording digits 0-9 in English. The results show that the digit speech recognition system that has been built gives the highest average value of 63% for digit 4 using wavelet daubechies DB3 and wavelet dyadic transform method. As for the comparison results of the wavelet decomposition method used, that the use of dyadic wavelet transformation is better than the wavelet package.
AI at the Edge for Sign Language Learning Support

In the field of multimodal communication, sign language is and continues to be, one of the most understudied areas. Thanks to the recent advances in the field of deep learning, there are far-reaching implications and applications that neural networks can have for sign language mastering. This paper describes a method for ASL alphabet recognition using Convolutional Neural Networks (CNN), which allows to monitor user’s learning progress. American Sign Language (ASL) alphabet recognition by computer vision is a challenging task due to the complexity in ASL signs, high interclass similarities, large intraclass variations, and constant occlusions. We produced a robust model that classifies letters correctly in a majority of cases. The experimental results encouraged us to investigate the adoption of AI techniques to support learning of a sign language, as a natural language with its own syntax and lexicon. The challenge was to deliver a mobile sign language training solution that users may adopt during their everyday life. To satisfy the indispensable additional computational resources to the locally connected end- user devices, we propose the adoption of a Fog-Computing Architecture.
Post-Zoom: Screen Environments and the Human/Machine Interface

Digital technologies like Zoom have become one of the hallmarks of the Covid-19 pandemic, ensuring that architects and scholars stay connected to each other while reconstructing old and new ways of...
Analysis of MEMS-IMU Navigation System Used in Autonomous Vehicles

In this study, it is aimed to perform a COMSOL analysis of the inertial measurement unit (IMU), which is a sensor based on a microelectromechanical system (MEMS) in an inertial navigation system (INS).Autonomous vehicles are the types of vehicles that can go on the move without the intervention of the driver by detecting the road, traffic flow, and environment without the need of a driver, thanks to its automatic control systems, software algorithms, and intelligent sensor structures.Autonomous vehicles can detect objects around them using technologies and techniques such as radio detection and ranging (RADAR), light imaging detection and ranging (LIDAR), Global Positioning System (GPS), INS, ultrasonic sensors, camera systems, and computer vision.After providing information about the use of IMU sensors in autonomous vehicles, the finite element analysis of the gyroscope sensor by the COMSOL program was performed in this study.
Towards a Smart Toy Ecosystem for Pets

When pet's owners take care of their pets, it sparks the need to know about the well-being of their pets.This requires the ability to monitor the animals' activities in order to recognize unexpected behavior of the pets.Such monitoring systems are also useful for pet training purposes, which could be extended to more intelligent systems used to encourage specific behavior of pets.In order to do so, this study aims to develop a system that can keep track and record of such data of pets (e.g.movements, body temperature).The proposed eco-system includes a collar affixed to the pet, interacting with a mobile application, a cloud data storage and processing platform as well as other toys to communicate with.This system is designed to be easily extended with new toys.It also can interact with smart voice assistant systems such as Apple Siri or Amazon Alexa.In addition, it has light weight so it can be affixed to small dogs or cats.
Simplifying the multi-GPU programming of a hyperspectral image registration algorithm

Hyperspectral image registration is a relevant task for real-time applications like environmental disasters management or search and rescue scenarios. Traditional algorithms for this problem were not really devoted to real-time performance. The HYFMGPU algorithm arose as a high-performance GPU-based solution to solve such a lack. Nevertheless, a single-GPU solution is not enough, as sensors are evolving and then generating images with finer resolutions and wider wavelength ranges. An MPI+CUDA multi-GPU implementation of HYFMGPU was previously presented. However, this solution shows the programming complexity of combining MPI with an accelerator programming model. In this paper we present a new and more abstract programming approach for this type of applications, which provides a high efficiency while simplifying the programming of the multi-device parts of the code. The solution uses Hitmap, a library to ease the programming of parallel applications based on distributed arrays. It uses a more algorithm-oriented approach than MPI, including abstractions for the automatic partition and mapping of arrays at runtime with arbitrary granularity, as well as techniques to build flexible communication patterns that transparently adapt to the data partitions. We show how these abstractions apply to this application class. We present a comparison of development effort metrics between the original MPI implementation and the one based on Hitmap, with reductions of up to 95% for the Halstead score in specific work redistribution steps. We finally present experimental results showing that these abstractions are internally implemented in a high efficient way that can reduce the overall performance time in up to 37% comparing with the original MPI implementation.
Voice Identification Using MFCC and Vector Quantization

The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pitch, tone, and frequency. The speaker's models are created and saved in the system environment and used to verify the identity required by people accessing the systems, which allows access to various services that are controlled by voice, speaker identification involves two main parts: the first part is the feature extraction and the second part is the feature matching.
The necessity of a lead person to monitor development stages of the DevOps pipeline

&lt;span&gt;The Development-to-Operations model, known as DevOps, refers to a framework that integrates the development and operation phases of organizational applications. DevOps bridges the gap between these two processes that traditionally prolonged the implementation of these applications. This framework aims at enhancing service delivery and releasing subsequent updates based on real-time customer feedback. Consumers in this modern era prefer tailor-made services, and a slight downtime from one supplier can quickly shift their preference to the company’s competitors. However, DevOps involves sophisticated coding activities, and there is a need for someone to oversee these processes to ensure developers are not overwhelmed. The objective of this survey is to clarify the significance of a lead person to monitor the DevOps pipeline and report any failure detected in each development stage. The study utilized meta-analysis of verified tertiary resources from other researchers that took a deep dive into the DevOps model and how it works towards organizational goals in various firms. All institutions involved in multiple business platforms should take advantage of new technologies to scale up their service delivery and net profit. If adopted and appropriately monitored, DevOps can revolutionize the capabilities of most business applications by minimizing downtimes and providing uninterrupted services.&lt;/span&gt;