Reviewerly/exHarmony huggingface dataset:
Seed Words Based Data Selection for Language Model Adaptation

We address the problem of language model customization in applications where the ASR component needs to manage domain-specific terminology; although current state-of-the-art speech recognition technology provides excellent results for generic domains, the adaptation to specialized dictionaries or glossaries is still an open issue. In this work we present an approach for automatically selecting sentences, from a text corpus, that match, both semantically and morphologically, a glossary of terms (words or composite words) furnished by the user. The final goal is to rapidly adapt the language model of an hybrid ASR system with a limited amount of in-domain text data in order to successfully cope with the linguistic domain at hand; the vocabulary of the baseline model is expanded and tailored, reducing the resulting OOV rate. Data selection strategies based on shallow morphological seeds and semantic similarity via word2vec are introduced and discussed; the experimental setting consists in a simultaneous interpreting scenario, where ASRs in three languages are designed to recognize the domainspecific terms (i.e. dentistry). Results using different metrics (OOV rate, WER, precision and recall) show the effectiveness of the proposed techniques.
The Effect of Make a Match Technique Towards Students’ Reading Skill in Narrative Text at The Second Semester Ninth Grade Of SMPN 1 Tanjungpinang

The purpose of this study is to know the effect make a match technique towards students’ reading skill in narrative text at the second semester ninth grade of SMPN 1 Tanjungpinang. The design of the research that researcher used in thisstudy are quasi-experiment non equivalent (Pre-test and Post -test) with the quantitative approach. The sample of this study is 68 students’ taken from the ninth grade SMPN 1 Tanjungpinang who are selected through with cluster random sampling technique. This research sample was two classes consisting of 34 students’ for the experimental class and 34 students’ for the control class. In the experimental class, researcher used make a match technique and the control class the researcher used speech technique to teach students’. The treatment was held in 2 meetings where 4x40 minutes to teach each class. In collecting data, researcher conducted pre-test and post-test by presenting multip le choice test consisting of 20 items for each test. Data were analyzed using Minitab 17 to calculated the t -test. The results of statistical calculations, the average score of pre-test in the experimental class were 72.06 and 87.06 for the post -test. Meanwhile, the average score of the pre-test in the control class were 59.26 and 75.00 for the post-test. In addition, in the hypothesis test table, it can be seen that ά = 0.05. This proves that the null hypothesis (Ho) is rejected and the alternative hypothesis (Ha) is accepted because p-value>0.05. It means that there is an effect of make a match technique towards students reading skill in narrative text at the second semester ninth grade
Cybersecurity impacts of the Covid-19 pandemic in Italy

The Covid-19 pandemic has pushed companies to the extensive use of digital services, to implement home working and provide online services to people in lockdown. As a consequence, it is interesting to study how this has affected the number, kind and distribution of cybersecurity attacks. This paper gives an empirical evaluation of the cybersecurity attacks at the beginning of the Covid-19 pandemic in Italy, based on data collected from the questionnaires of the annual Digital Attacks Observatory. It shows that the overall number of attacks has not increased, but attacks have affected smaller companies than before. This can be explained with the fact that the Italian industrial scenario is mostly populated by small and medium enterprises, that have been obliged to a quick reconversion of their IT systems and typically lack the necessary cybersecurity culture. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Pfeiffer Library: Accessing Pfeiffer Library: DragonQuest

Tutorials on how to log into your online accounts at Tiffin University and Pfeiffer Library
Sentiment Analysis of Online Food Reviews using Big Data Analytics

Nowadays sentiment analysis has become very important, mostly used for huge datasets and helpful for researchers for applying methods and techniques. Amazon’s food data is growing exponentially and traditional systems are unable to process it, so we used Big Data to overcome this problem. In this paper, we explore different methods and techniques of sentiment analysis using apache spark data processing system for big datasets of Amazon Fine Food reviews. Three mechanisms are applied that have more than 80% accuracy named as Linear SVC, Logistic Regression, and Naive Bayes by using MLlib which is Apache Spark’s library for ML. When applied these methods we realize that Linear SVC performs efficiently than NB and logistic regression.
Ανάλυση εικόνας (σπεκτρογράμματος), βιοσημάτων και χαρακτηριστικών έκφρασης για ανίχνευση άγχους

Stress is a dominant factor that plays massive role to person`s performance and mental condition. During the last decades, many researchers have pointe out the negative effects of mental stress. That is why it is mandatory to monitor stress from its manifestation, so the negative effect could be counter measured. In working environments, where employees are required to undertake multiple duties in order to achieve their goals, stress is a common emotion which leads to lack of concentration and performance. Because of the amount of responsibilities, worker`s stress should be held to the minimum range in order to increase productivity. The purpose of the specific study is to propose an effective way to detect and recognize stress conditions of employees during their duties. Monitoring is performed by multiple sensors, wearable and not, which give the necessary information to the decision system. After the emergence of wearable devices that could be part of our lives, because of their capability for continuous health-care monitoring using low-energy, researchers have started a great amount of experiments that prove the existence of extreme stress of individuals during daily routines. The last years, during the extremely fast rise of machine learning access from the most of researchers, a variety of modern machine learning techniques are being d in order to achieve maximum system efficiency, using the preprocessed information from the sensors.
The Available Resources and Capabilities Are a Means of Attracting Sports Investment in the Diwaniyah Club

The purpose of the study: is preparing a questionnaire form for available resources and capabilities as a means of attracting sports investment in the Diwaniyah club. Identify the importance of the expressions prepared in the questionnaire form for the available resources and capabilities as a means of attracting sports investment in the Diwaniyah Club. To achieve the objectives of the research, the researcher used the descriptive method in the survey method, and the research sample was selected using the comprehensive enumeration method by (160) individuals, who were distributed by (8) members of the board of directors, (20) of the club's employees (5) founding members, (121) individuals. Members of the assisting body, businessmen (6) individuals, and then the researcher used the questionnaire form as a basic tool for collecting data, and among the most important findings of the researcher is that the availability of financial capabilities to finance the infrastructure as well as advertising, all of this works to attract investors.
Extensible Path Planning Intelligent System by Applying Nature Inspired Computing (NIC) Algorithm

The mobile robot path planning is a central problem in several areas such as modern industry and cyber physical systems. This requires an embedding intelligence into that robotics for ensuring feasible solutions to task execution. Many researchers developed an optimization algorithm for finding shortest path in known environment.In this proposed paper by applying extensible particle swarm optimization (EPSO) algorithm for a mobile robot to avoid obstacles without collision in a path to reach target (destination) in a small amount of time.The performance results of proposed EPSO algorithm shows better results with conventional algorithms to reach destination with minimum energy consumption and also minimize time.
Annotating Entities with Fine-Grained Types in Austrian Court Decisions

The usage of Named Entity Recognition tools on domain-specific corpora is often hampered by insufficient training data. We investigate an approach to produce fine-grained named entity annotations of a large corpus of Austrian court decisions from a small manually annotated training data set. We apply a general purpose Named Entity Recognition model to produce annotations of common coarse-grained types. Next, a small sample of these annotations are manually inspected by domain experts to produce an initial fine-grained training data set. To efficiently use the small manually annotated data set we formulate the task of named entity typing as a binary classification task – for each originally annotated occurrence of an entity, and for each fine-grained type we verify if the entity belongs to it. For this purpose we train a transformer-based classifier. We randomly sample 547 predictions and evaluate them manually. The incorrect predictions are used to improve the performance of the classifier – the corrected annotations are added to the training set. The experiments show that re-training with even a very small number (5 or 10) of originally incorrect predictions can significantly improve the classifier performance. We finally train the classifier on all available data and re-annotate the whole data set.
A Dynamic Searchable Symmetric Encryption Scheme using Cloud

Searchable encryption has gotten a major thought from the assessment partner with various types of progress being proposed, each accomplishing asymptotically ideal multifaceted nature for express estimations. Dismissing their clean, the consistent ambushes and sending endeavors have displayed that the ideal asymptotic multifaceted plan may not normally infer reasonable execution, particularly if the application requests a high security. In this article, we present a novel Dynamic Searchable Symmetric Encryption framework called Incidence Matrix, which achieves a raised degree of security, functional interest/update, and low client accumulating with veritable blueprints on ensured cloud settings. We handle an event arrange close to two hash tables to make an encoded record, on which both request and strengthen errands can be performed sufficiently with unimportant data spillage. This basic arrangement of information structures inconceivably offers a central level of DSSE security while accomplishing sensible execution. In specific, IM-DSSE achieves forward-security, in this way around assurance and size-absence of respect at the same time. We in like manner make a couple DSSE combinations, each offering explicit tradeoffs that are fitting for different cloud applications and establishments. We totally completed our structure and evaluated its introduction on a veritable cloud system (Amazon EC2). We have released IM-DSSE as an open-source library for wide development and change.
Methodology to Monitor Intellectual and Personal Resource of Foreign Military Specialists Studying at the Russian Higher Military Aviation School

The research objective includes developing methodology to monitor foreign military specialists’ intellectual and personal resource. The article proposes an authorial approach to evaluating professional training quality at the Russian higher military aviation school. Scientific originality of the study lies in the fact that the author for the first time identifies structural and meaningful characteristics of the methodology to monitor foreign military specialists’ intellectual and personal resource. The research findings are as follows: the author suggests his own methodology to monitor intellectual and personal resource of foreign military specialists studying at the Russian higher military aviation school, introduces the notion “foreign military specialist’s intellectual and personal resource” into pedagogy of professional education.
A dinâmica terapêutica do grupo virtual de ouvidores de vozes como dispositivo de saúde mental

The study seeks to deepen what is practiced today following currents based on antipisiquitry, which it was configured in a chain whose main characteristic was to promote alternative ways of treating psychological suffering (CHARLESWORTH, 1980). In order to promote a break with the psychiatric asylum model, the use of alternative strategies and guidelines comes with the aim of promoting the social inclusion of the crazy, proposing a new approach to madness (BRASIL, 2004). Thus, several strategies are adopted that seek to promote the insertion of users through different dynamics, as well as mutual aid groups. From the perspective of mutual aid health groups, there is the existence of Voice Hearing Groups (BAKER, 2016). The general objective of the study is to analyze the therapeutic dynamics in mental health of groups of voiced listeners. To achieve this, the following specific objectives were outlined: To identify emerging themes in the groups; evaluate the dialogicity profile of the groups and evaluate challenges and potentialities in the use of the virtual modality via internet. This is a qualitative, descriptive study. The scenario chosen for the study was established through online groups of Voice Hearers. The online modality was chosen due to the recommendation of social isolation resulting from the Pandemic by Covid-19 during the period of production of this research. As inclusion criteria, the following were established: people over 18 years of age who have participated in the Voice Hearing Group for more than a month, who voluntarily accept to participate in the research and have access to the Internet. There are no exclusion criteria for participants. The results presented in the study show that the virtual groups of voice listeners have great therapeutic potential, being involved in the relationship of the listeners with the voices and in their relations with the world, favoring their identification with the other members. In short, it is concluded that the elements of the approach of the group of listeners of voices provide the production of therapeutic spaces, linked or not to a mental health service, but that is responsible and effective in the dissemination of scientific care.
Security and Practical Models for Quantum Key Distribution

This report reviews two quantum key distribution (QKD) protocols: the BB84 protocol and the measurement device independent (MDI) QKD protocol. The goal of this report is to recreate the security proof of the BB84 protocol, to generate the secret key rate for a practical application of the BB84 protocol, both with and without decoy states, and to review the MDI-QKD protocol and look at the advantages it has for practical QKD. The proof security of the BB84 protocol is done by designing an equivalent theoretical protocol and proving its security by bounding the information of the eavesdropper to an exponentially small number. The best distance over which secret key rate can be generated with the practical model of the BB84 protocol that is presented in this report, is 165 km. This is achieved by employing decoy states and is more than three times as far as the model can achieve without decoy states, which gave a distance of 52 km at best. The zero distance key rate of the model with decoy states is R = 1.21 · 10-2 bits per pulse (bpp), at best. This is an order of magnitude larger than R =1.02 · 10-3 bpp, which is what the model without decoy states could produce. The decoy state method is therefore an improvement for practical QKD. By reviewing the MDI-QKD protocol it can be concluded that because it eliminates the measurement device side channels, it is very useful for practical QKD, since it makes security analysis simpler and more precise. It also necessarily employs decoy states, which improves the secret key rate. MDI-QKD therefore is a promising protocol to use for future quantum communications.
Improving your skills in writing short stories through cartoon visual media

Learning to write short stories that are only theory-oriented makes students feel bored and even afraid. The skills of writing short stories for fourth-grade students have not shown maximum results. Teachers have not been able to cultivate interesting and fun learning because they only use the lecture method. The purpose of this study was to improve the skills of writing short stories using cartoon visual media in grade IV SDN Temaji III, Jenu District, totaling 26 children. This type of research is descriptive research with data collection techniques in the form of comparison of observations, interviews, and tests from each cycle. The data analysis technique used is qualitative and quantitative data analysis. Based on the results of research in the first cycle, students who completed writing short stories were 65% while in the second cycle it was 92%. So it can be concluded that visual cartoon media has been proven to improve short story writing skills in grade IV SDN Temaji III both in the process and the results.
Data Augmentation for Sign Language Gloss Translation.

Sign language translation (SLT) is often decomposed into video-to-gloss recognition and gloss to-text translation, where a gloss is a sequence of transcribed spoken-language words in the order in which they are signed. We focus here on gloss-to-text translation, which we treat as a low-resource neural machine translation (NMT) problem. However, unlike traditional low resource NMT, gloss-to-text translation differs because gloss-text pairs often have a higher lexical overlap and lower syntactic overlap than pairs of spoken languages. We exploit this lexical overlap and handle syntactic divergence by proposing two rule-based heuristics that generate pseudo-parallel gloss-text pairs from monolingual spoken language text. By pre-training on this synthetic data, we improve translation from American Sign Language (ASL) to English and German Sign Language (DGS) to German by up to 3.14 and 2.20 BLEU, respectively.
THE INFLUENCE OF PEER EDITING ONLINE TOWARDS THE STUDENTS’ WRITING SKILL

Lots of students find the difficulties when they have to put their thoughts into writing. Moreover, when they need to do the proofreading and editing their own writing, this inevitably makes writing exceptionally tiring and distressing. In this study, researchers focused on a series of writing processes, especially editing and proofreading activities. The objective of this research was to find out the influence of Peer Editing online technique towards the students’ research proposal writing skill and to know and to describe whether the effectiveness of the students’ research proposal writing skill who learn through peer editing online is higher than those who learn through conventional technique. The research was conducted by using a quasi-experimental design with pretest and post-test. The population of this research are the students at the fifth semester of English education major at STKIP PGRI Bandar Lampung that consisted of 63 students in 2 classes. The sample of this research were two classes, they were as control class and experimental class. Control class was taught by Individual writing while experimental class was taught by peer editing online technique. In getting the data, the researchers used writing test. The result showed that based on the calculation, the researchers got that = 5.41 and = 2.00 and 2.66. It means that Ho is rejected and Ha is accepted. From the result above, the researchers state that there is an improvement and an significant influence of Peer editing online technique towards students’ research proposal writing skill.
AN ANALYSIS ON THE EIGHTH STUDENTS’ PERCEPTION OF THE APLICATION PPP (PRESENTATION, PRACTICE AND PRODUCTION) TECHNIQUE IN TEACHING WRITING DESCRIPTIVE TEXT

Based on the phenomena that students have difficulties in writing descriptive text, the students could not write because they do not have any ideas when they are asked to write. So, they need some ways which could help them in writing. The problems in writing can be solved by implementing some strategies in teaching writing. This research  aims at knowing the use of PPP (Presentation, Practice and Production) in teaching writing to the eighth grade students. This research is qualitative research. The subject of this research was the eighth grade students of one junior high school in Cimahi in the academic year of 2020 – 2021 which consisted of 31 students. The writer used a questionnaire to collect data. These findings reveal that the use of PPP (Presentation, Practice and Production) techniques in teaching writing in the classroom can improve students' writing abilities in the classroom. Based on the result of questionnaire the use of PPP (Presentation, Practice and Production) one of the right way to teach writing. It means that using make a match method was effective, and easier to be applied in teaching writing descriptive text. Keywords :  PPP (Presentation, Practice and Production), Teaching Writing, Students’ Ability
A Study on Scale Development and Feasibility of Masteristic Achievement

The purpose of this study is to conceptualize ‘masteristic achievement’ and to develop a scale to apply it to the workplace and verify its validity. First of all, the components and preliminary items were set up through prior research and then modified and supplemented by conducting two Delphi surveys on 24 experts. Then, a preliminary survey (219 people) and exploratory factor analysis were conducted for office workers with more than five years of experience, the main survey (526 people) was conducted to analyze the feasibility and reliability of masterity achievement, and the feasibility of the composition through the collection of opinions of expert group was met, ensuring the validity of the scale of masterity achievement. In addition, the structural equation model was formed through the verification factor analysis, and the statistical reliability was confirmed by the high conformity of the three-factor structure model. Finally, 19 questions of a total of three sub-factors (9 questions for ease of work, 5 questions for work performance, and 5 questions for pride in work) were selected as criteria for the masteristic achievement with theoretical implications, practical implications, limitations, and suggestions for future research. This study is the first attempt to measure masteristic achievement and will be an important foundation for studying the results of future work and learning phenomena in workplace.