Reviewerly/exHarmony huggingface dataset:
Experience in annotating connectives in Japanese text – lessons and prospects

This paper offers an overview of an attempt to annotate a text in Japanese with the aim of pointing out all possible connections between elementary chunks of discourse, and the connective devices marking them. Being the first experience in Japanese, it asks for a certain adjustment of the annotation rules already used in the existing schools. This primarily touches upon what entities are connected and also upon the definition of a connective. Furthermore, semantic areas covered by connectives also need correction if reviewed through an in-depth analysis of the speaker’s intentions. The obstacles met while carrying out the annotation, and the pervasive patterns revealed, focus around two linguistic factors. On the one hand, structural specifics of the Japanese language cause the speaker to forego multiple transformations warping the surface structure in order to attain linear development of his line of discourse. On the other hand, the genre of the linguistic material (a lecture in tourism marketing) is largely accountable for dominating Causality and Discourse Deployment areas of connectives. It is through those that a higher level of pragmatic motivation is achieved in the explicit markers of the text structure – which turns out crucial in making the speech more persuasive.
IoT based Smart Transportation System: Implementation and Security Challenges

With the increasing trend of digitalization, Internet of things (IoT) provide a way to make the system efficient and automated in every possible sector of daily human life. In this paper, the overview of IoT enabled application in the transportation sector is represented with some recent case studies. The recent work and challenges in the deployment of the IoT in the transportation application have also been demonstrated. Various cybersecurity such as secure data code, two factor authentication, end-to-end encryption and the use of anti-malware software to ensure the safe and secure operations of IoT devices are also explored.
Comparative Analysis of Server and Serverless Cloud Computing Platforms Vladyslav Kotyk, Yevhenii Vavruk

Cloud computing is emerging as a powerful computing paradigm for the efficient use of resources. However, decisions to move to cloud computing always remain risky from the customer's point of view, considering the benefits they get from it. Existing research on cloud computing is more focused on technical aspects such as security, quality, efficiency, etc. However, research on the implementation of cloud computing is at an early stage. Thus, in this article, an attempt is made to create a model for cost analysis and advantages for deciding on the application of cloud computing. It takes into account various organizational parameters, designing server and serverless architectures using Microsoft Azure Portal cloud platform services and policies of this organization. Also, it makes a comparative characterization of these services according to power and price criteria. A comparative description of these services according to capacity and price criteria is also given. It shows the structure of the test tool for assessment. Evaluation parameters and metrics are defined. In addition, this article contains information about approaches to evaluating cloud platforms according to various criteria that are most important for a developer.
Hybrid Quantum-Classical Autoencoders for End-to-End Radio Communication

Quantum neural networks are emerging as poten-tial candidates to leverage noisy quantum processing units for applications. Here we introduce hybrid quantum-classical au-to encoders for end-to-end radio communication. In the physical layer of classical wireless systems, we study the performance of simulated architectures for standard encoded radio signals over a noisy channel. We implement a hybrid model, where a quantum decoder in the receiver works with a classical encoder in the transmitter part. Besides learning a latent space representation of the input symbols with good robustness against signal degradation, a generalized data re-uploading scheme for the qubit-based circuits allows to meet inference-time constraints of the application.
UniMed: Multimodal Multitask Learning for Medical Predictions

Recently, deep learning techniques based on electronic health record (EHR) data have achieved success in medical prediction. However, due to the complexity, heterogeneity nature of EHR data, most previous studies build models based on single-modal data (e.g. the structured data or the unstructured free-text data). Although some studies have trained the models based on multimodal EHR data and achieved more advanced performance, they still suffer from the clinical practicability problems, as they require separate modeling for each medical prediction task. Moreover, they ignore the potential correlation between clinical prediction tasks. In this work, we propose UniMed, a Unified model handles multiple Medical prediction tasks simultaneously by learning from multimodal EHR data. Our UniMed model encodes each input modality separately and uses a transformer decoder followed by task-specific prediction heads to predict each medical task. Experimental results conducted on publicly available EHR dataset demonstrate that there is a time-progressive correlation between medical prediction tasks and show the effectiveness of our method.
Comparative Approach of Sentiment Analysis Algorithms to Classify Social Media Information Gathering in the Spanish Language

This research provides a perspective on the large amount of information shared by millions of people, who express feelings and opinions on social networks. This investigation gathered data from the social network Twitter, employing the API v2 during the month of June of 2022, concerning topics of local economic indices in Peru, with the aim to identify the precision of the different sort algorithms from analysis of feelings (SA) for the Spanish language. Tweets collected that conformed to the Corpus Data from the study were processed using the Natural Language Processing (NLP); next, they vectorizaron with the Bag method of Words (BOW) which allowed them to construct a vocabulary of 4045 tokens clean, marking the absence (0) and it is present at (1) of the word in tweets with support of bookstores of software RStudio. Finally, it was come to compare three techniques of analysis of feelings (SA) in Machine Learning (Naïve Bayes, Support Vector Machine and K-Nearest Neighbors). The results indicate a 92.13% accuracy ratio for Naïve Bayes (NB) (F1 score = 0.90026135), 93.11% for Support Vector Machine (SVM) (F1 score = 0.90026135), and 91.71% for K-Nearest Neighbors (KNN) (F1 score = 0.90026135). The results indicate that the most optimal classification technique was the SVM with an accuracy of 95.15%, making it possible to identify the best technique for classifying feelings in Spanish, applied in a thematic environment related to topics of economic indicators (e.g., inflation, unemployment, dollar) in the Peruvian context.
Role of Communication and Language in Building Capacity for Different Sectors of the Nigeria Economy: Study of Media Sub-Sector

Training and re-training in every sector is the purveyor of growth and enhancement in every sector of economies in the world. It is the platform, frontier and bedrock on which diverse economies flourish. What it, therefore, means is that success in this sector predominantly is hinged on the ability of the various sectors to give unfettered attention and access to its workforce to training and retraining with very strong and extensive latitude. By so doing, the humans who are vested with the ample responsibility of delivering capacity would have being equipped tremendously and, empowered, advanced, enhanced and positioned to achieve the prescribed goods, which will not only impact on the humans, but promote economic development and growth. To achieve all of these, there are roles parts of human life should contribute to. Communication and language are parts of human life presumed to have the capacity to enhance growth in the existence of any country. It is believed that communication and language can achieved this through the display of litany of arsenals in their kit. It is, therefore, these arsenals that communication and language possess that this study aims at exploring, using the descriptive method to unravel the plethora of roles communication and language can offer for the growth of economies in the world and particularly Nigeria using the prescribed medium that will impact effectively to the target audience.
Steganography Encryption Secret Message in Video Raster Using DNA and Chaotic Map

Recently, much secured data has been sent across the internet and networks. Steganography is very important because it conceals secure data in images, texts, audios, protocols, videos, or other mediums. Video steganography is the method of concealing data in frames of video format. A video is a collection of frames or images used for hidden script messages. This paper proposes a technique to encrypt secret messages using DNA and a 3D chaotic map in video frames using the raster method. This technique uses three steps: Firstly, converting video frames into raster to extract features from each frame. Secondly, encryption of secret messages using encoded forms of DNA bases, inverse/inverse complements of DNA, and utilizing 3D chaotic maps, Thirdly, hiding encryption secret messages in that raster video frame by using a secret key in the four corners of each video frame. This technique hides large amounts of secret data because the video frame is large and accepts any message size. The outcomes are efficient, robust, highly secure, and can tolerate high capacity. These outcomes have been obtained from a set of tests like: peak signal to noise ratio (PSNR), mean square error (MSE), entropy, correlation coefficient, and histogram and capacity.
PENGARUH KECAKAPAN LITERASI DIGITAL TERHADAP KINERJA GURU SEKOLAH MENENGAH KEJURUAN DI KABUPATEN GOWA

This research was conducted with the aim of knowing the effect of digital literacy skills on the performance of Vocational High School teachers. The population in this study were all teachers who were civil servants at the State Vocational High School in Gowa Regency, totaling 238 teachers. The proportional random sampling technique was carried out in obtaining a research sample of 70 teachers who had previously used the slovin formula in determining the minimum number of research samples. questionnaire is an instrument in this research which in its development process is tested for content validity using the Gregory formula, construct validity using a confirmatory factor analysis (CFA) technique with a maximum likelihood approach, as well as testing the reliability of the instrument using the Cronbach alpha formula which produces a reliability coefficient value of 0.98 for the teacher's digital literacy skill instrument and a reliability coefficient value of 0.95 for the teacher's performance instrument. Simple linear regression technique was used to analyze the data obtained. The results of the study reveal that there is a positive and significant effect of digital literacy skills on the performance of Vocational High School teachers, and the contribution or influence of digital literacy skills on teacher performance is 39%.
Improve Vocabulary by Using Media Animated the Folklore of Malin Kundang

In addition to local expertise that we must conserve, such as folklore, the rapid growth of technology in the field of education makes learning easier through tools like audio-visual animation media. Malin Kundang is just one example of the many varieties of folklore that exist. The goals of this research are threefold: (1) to determine whether or not students can benefit from learning about Malin Kundang folklore; (2) to use Malin Kundang folklore as a means to expand vocabulary; and (3) to determine whether or not using Malin Kundang folklore can be used to improve learning outcomes. In this work, we employ quantitative techniques. In order to describe events, establish links, or test hypotheses, quantitative research relies on the collection and analysis of numerical data. A student survey is one example of such a device. The researcher employed SPPS to perform the necessary calculations. Students' comprehension of the English language is significantly improved when they are exposed to animated media based on malin kundang folklore, according to a review of the available research.
Development of Nonparametric Structural Equation Modeling on Simulation Data Using Exponential Functions

This study aims to determine the development of nonparametric SEM analysis on simulation data using the exponential function.Methodology: This study uses simulation data which is defined as an experimental approach to imitate the behavior of the system using a computer with the appropriate software.This study uses nonparametric structural equation modeling (SEM) analysis.The function used in this study is the exponential function.Results: The results showed that with simulation data all relationships have a significant effect on each other which have formative and reflective indicators.Testing the direct effect of Y2 on Y3 produces a structural coefficient value of 0.255 with a p-value <0.001 which means it is significant.The structural coefficient is positive, indicating that the relationship between the two is positive.This means that the higher Y2, the higher Y3.The results of the measurement model get a coefficient of determination of 0.91.It can be explained that 91% of the diversity of variables Y1, Y2, and Y3 can be explained by the X1 variable while 9% is explained by other variables not used in the model.Novelty: This study uses simulation data that is made very complex to analyze several related system structures at one time and can use a lot of data to get closer to real conditions to obtain comprehensive results, adjust to the criteria to be studied, and meet the following criteria: nonparametric SEM analysis criteria using the exponential function.
Simultaneous Action Recognition and Human Whole-Body Motion and Dynamics Prediction from Wearable Sensors

This paper presents a novel approach to solve simultaneously the problems of human activity recognition and whole-body motion and dynamics prediction for real-time applications. Starting from the dynamics of human motion and motor system theory, the notion of mixture of experts from deep learning has been extended to address this problem. In the proposed approach, experts are modelled as a sequence-to-sequence recurrent neural networks (RNN) architecture. Experiments show the results of 66-DoF real-world human motion prediction and action recognition during different tasks like walking and rotating. The code associated with this paper is available at: github.com/ami-iit/paper_darvish_2022_humanoids_action-kindyn-predicition
Boosting the Revealing of Detected Violations in Deep Learning Testing: A Diversity-Guided Method

Due to the ability to bypass the oracle problem, Metamorphic Testing (MT) has been a popular technique to test deep learning (DL) software. However, no work has taken notice of the prioritization for Metamorphic test case Pairs (MPs), which is quite essential and beneficial to the effectiveness of MT in DL testing. When the fault-sensitive MPs apt to trigger violations and expose defects are not prioritized, the revealing of some detected violations can be greatly delayed or even missed to conceal critical defects. In this paper, we propose the first method to prioritize the MPs for DL software, so as to boost the revealing of detected violations in DL testing. Specifically, we devise a new type of metric to measure the execution diversity of DL software on MPs based on the distribution discrepancy of the neuron outputs. The fault-sensitive MPs are next prioritized based on the devised diversity metric. Comprehensive evaluation results show that the proposed prioritization method and diversity metric can effectively prioritize the fault-sensitive MPs, boost the revealing of detected violations, and even facilitate the selection and design of the effective Metamorphic Relations for the image classification DL software.
Verification of Quantum Circuits

We are at the dawn of a new “computing age” in which quantum computers will find their way into practical applications. Although quantum computers work differently than classical machines, the design flow for realizing applications is similar: first, the desired functionality/application is described on a high level. Then, it is compiled down to a description (usually called quantum circuit) that can be executed on an actual machine. During this process, lots of constraints have to be fulfilled, and optimizations are applied to reduce the circuit’s size and, hence, improve the actual performance on the quantum computer – all of which are highly nontrivial steps. As in conventional design, sooner or later, it is essential to check whether the resulting realization is correct – motivating verification. This chapter reviews and provides a summary of work in this regard. Considering the challenges currently seen in the verification of (comparatively simpler) classical systems, this may provide the basis for preventing the emergence of a verification gap in quantum computing.
IMPLEMENTATION OF REWARDS IN JUNIOR HIGH SCHOOL STUDENTS IN VOCABULARY LEARNING

The main focus of this research is the application of rewards in vocabulary learning. The purpose of this study was to determine the application of the reward method by the teacher in learning vocabulary. The researcher used a qualitative approach with a descriptive case study design. Data collection techniques used are observation, interviews, and documentation. To analyze the data, the researcher followed the steps described by Miles &amp; Hubberman. These steps are: data reduction, data presentation, and drawing conclusions/verification. Through this investigation, the researcher found that when applying the reward method in vocabulary learning, the teacher did 6 stages. That is preparing the material, explaining the material, giving questions or games, giving rewards to students who take lessons well and answer questions correctly, providing opportunities to answer questions for students who are not focused, and adjusting the number of questions to the amount of the reward given.
PEMANFAATAN MEDIA SOSIAL DALAM UPAYA MENINGKATKAN PENERIMAAN SISWA BARU DI SMA SWASTA

Competition between schools in the world of education is in fact unavoidable. The competition is getting more intense every year given the emergence of many private schools. For private schools, especially at the high school level, the most crucial thing is how to increase public interest, which is expected to have a direct impact on increasing new student admissions at the school. Social media is considered as one of the strategies that has a strong impact in efforts to increase the acceptance of new students in the midst of increasing competition between schools, especially in private high schools which are increasingly emerging lately. This research method is descriptive qualitative. The subjects of this study were 2 people including the head of the new student admissions team in high school, namely the Deputy Head of Public Relations, and the head of a private high school. The object of this research is the school's social media. The results of this study show that various social media are used such as Instagram, Facebook, Twitter, Youtube, and Tiktok. The social benefits in increasing new student admissions are for school promotion media, branding, reaching a wide area more effectively and increasing the interest of prospective students. Social media management must also be considered to maximize the use of social media in increasing new student admissions.
KOMPETENSI LITERASI DIGITAL SISWA DALAM PEMBELAJARAN DARING DI SMP NEGERI 2 KABANJAHE

This study aims to describe the skills and abilities of students in using digital media and to find out the obstacles experienced by students as well as the efforts made by teachers in improving skills in online learning. This research uses desciptive qualitative method. It applies the observation, and interviews to get the data. The result shows that: the use of digital media in SMP Negeri 2 Kabanjahe includes the ability to connect in online learning, the ability to communicate in online learning and the ability to do and submit the assignments in online learning. Evaluation of information content includes a student's ability to think critically and provide an assessment of what is found online accompanied by the ability to identify the validity and completeness of information. Producing information content includes the ability to produce or create content such as Facebook, writing on a blog or website, create video clips using images or audio, or other forms of content.
ANALISIS BUTIR SOAL ULANGAN HARIAN KEMAGNETAN DAN INDUKSI ELEKTROMAGNETIK KELAS IX SMP

This study aims to determine the quality of the questions used in the daily tests on magnetism and electromagnetic induction for class IX in junior high school. The number of questions analyzed was 10 multiple-choice questions and 5 essay questions. The analysis technique for the quality of the items was carried out through a quantitative descriptive approach with the criteria for the quality of the questions which included validity, reliability, item discrimination, and the degree of difficulty of the questions which were carried out on 108 students. Through the results of calculations and analysis, data is obtained that all questions are valid and have high reliability, with a PG reliability value of 0.64 and essay reliability of 0.65. The results of the analysis of the degree of difficulty of the 15 PG questions and essays were that there were 3 questions (20%) in the easy category, 11 questions (73.3%) in the moderate category, and 1 item (6.7%) in the difficult category. The discriminating power analysis of 15 PG questions and essays obtained 4 very good questions (26.7%), 7 good questions (46.7%), 3 fairly good questions (20%), and 1 poor question (6.6%).