Reviewerly/exHarmony huggingface dataset:
Texting V/S face to face communication: a critical study and the stress levels associated with it

In the present age, Texting has become an inseparable and unavoidable part of one’s life. It has modified the manner in which we communicate and socialize. It is not only the most frequently used tool of communication, especially among the youth, but also it has developed into a scale or a technique to feel collective. Thus ushering us to analyze its benefits and the extent to which helps us to choose this form of communication over others, namely, face to face. This paper critically analyses two methods of communication: texting and Face to Face communication, between males and females, comparatively and the stress levels associated with both if any. The study focuses on factors that direct people towards using either of these tools of communication and it’s consequences on their stress levels. The research conducted consists of 100 participants,50 males and 50 females, aged 18 to 24, from diverse backgrounds. The research instruments used are questionnaires and the Perceived Stress Scale by Sheldon Cohen which has 10 items. The findings of this study depicted that the participants, both males, and females, are aware that texting is stressful as a form of communication and has more drawbacks for them compared to a face-to-face conversation and also the conflict between their preferences and actual usages. The study also aims to analyze how one form affects another in this aspect along with means through which the negative implications and stress be tackled, helping us use these convenient forms of communication to its fullest, in a healthy manner.
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL.

Meta-reinforcement learning (meta-RL) has proven to be a successful framework for leveraging experience from prior tasks to rapidly learn new related tasks, however, current meta-RL approaches struggle to learn in sparse reward environments. Although existing meta-RL algorithms can learn strategies for adapting to new sparse reward tasks, the actual adaptation strategies are learned using hand-shaped reward functions, or require simple environments where random exploration is sufficient to encounter sparse reward. In this paper, we present a formulation of hindsight relabeling for meta-RL, which relabels experience during meta-training to enable learning to learn entirely using sparse reward. We demonstrate the effectiveness of our approach on a suite of challenging sparse reward goal-reaching environments that previously required dense reward during meta-training to solve. Our approach solves these environments using the true sparse reward function, with performance comparable to training with a proxy dense reward function.
Difficulties and Strategies in Pronouncing English Vowels: an Investigation of EFL Students with Diverse Ethnicities

This study depicts students difficulties with diverse ethnicities in pronouncing English vowels at Universitas Muhammadiyah Surakarta. The type of this research is descriptive qualitative. The researchers employed interview to collect data from the students. The theory referred to Harmer (2007) categorizing the problems in learning pronunciation, namely hearing problem, utterance problem, and intonation problem was used to analyse the data. The subjects of the research were the eighth-semester students of English Education Department, Faculty of Teacher Training and Education at Universitas Muhammadiyah Surakarta. The results show that some students faced hearing, intonation, and problems; whereas others encountered a little problem in utterance. To cope with these, the students found strategies as follows: 1) reading activities to get used to pronouncing the correct vowels, 2) practice with friends to get direct corrections and 3) drilling methods as the easiest way to do.
LibGuides: Landing Your Dream Job: Networking

This guide is based on information provided by Jan-Marie Lanuzza, Experiential Education Coordinator and Jean Moats, Director of Library Services.
Content Validation of an Instrument Used to Assess the Educational Quality of Blended Learning Courses

This article describes the content validation process of an instrument used to assess the educational quality of training designs based on the Blended Learning model. The Expert Judgement technique was applied, involving the participation of 11 judges who have been duly trained in the design, implementation, and assessment of the Blended Learning model. The judges assessed the items presented based on criteria of relevance and clarity. The level of inter-judge agreement was determined using the Coefficient of Variation (CV) and Kendall's W test. The results show significant agreement amongst the participating judges regarding the relevance and clarity of the items that comprise the proposed instrument. The development of this research provides the design of an instrument able to objectify and define the educational quality of Blended Learning from a global and systemic perspective. This research project will help ensure quality in designing and implementing educational processes in hybrid learning environments and educational transformation and improvement in higher education. Keywords: blended learning, content validity, educational quality, expert judgement, higher education.
Analisis Iklim Komunikasi dalam Menumbuhkan Berbagi Pengetahuan di Perpustakaan Daniel S. LEV

Penelitian ini menganalisis faktor iklim komunikasi organisasi dalam menumbuhkan berbagi pengetahuan di perpustakaan Daniel S . Lev yang merupakan perpustakaan khusus literatur hukum dan politik. Iklim komunikasi pada penelitian ini menggunakan dimensi iklim komunikasi organisasi yang dicetuskan oleh Charles W. Redding . Penelitian ini menggunakan pendekatan kualitatif dengan menggunakan metode studi kasus. Adapun Informan pada penelitian ini yakni k epala perpustakaan dan seluruh staf perpustakaan. Hasil dari penelitian ini menunjukkan bahwa kelima nilai dari dimensi iklim komunikasi Redding memiliki andil dalam menumbuhkan kegiatan berbagi pengetahuan di perpustakaan Daniel S. Lev. Kegiatan berbagi pengetahuan yang tumbuh antara lain terlihat pada rapat mingguan, laporan, presentasi aktivitas, publikasi, pendampingan, dan sharing ketika bekerja. Nilai keterbukaan dan nilai tujuan kinerja tinggi menjadi nilai yang dominan. Abstract This study analyzes the factors of organizational communication climate in fostering knowledge sharing in Daniel S. Lev library which is a special library of law and political literature. This study was examined using the dimensions of organizational communication climate that was coined by Charles W. Redding, wherein the concept there are five values; supportiveness, participation in decision making, trust and reliability, openness, and high-performance goals. This is qualitative research using the case study method. The informants of this research are the Head of the Library and all library staff. The results of this study indicate that the five values of the Redding communication climate dimension contribute to fostering knowledge sharing activities in the Daniel S. Lev library. Knowledge sharing activities that have grown include weekly meetings, reports, activity presentations, publications, mentoring, and sharing while working. The value of openness and the value of high-performance goals become the dominant values.
SENSE OF BELONGING IN ENGINEERING STUDENTS DURING COVID-19 PANDEMIC

Appears in: ICERI2021 Proceedings Publication year: 2021Pages: 749-753ISBN: 978-84-09-34549-6ISSN: 2340-1095doi: 10.21125/iceri.2021.0231Conference name: 14th annual International Conference of Education, Research and InnovationDates: 8-9 November, 2021Location: Online Conference
RANCANG BANGUN APLIKASI AUGMENTED REALITY SEBAGAI SARANA MEDIA PENYAMPAIAN INFORMASI CARA PEMBAYARAN MENGGUNAKAN METODE MARKERLESS

BPA (Marketing and Admission Department) is an institution that provides information services to the public regarding STT PLN. Information on how to pay is published by BPA through social media in the form of pictures. With the limitations of the image media in terms of size and less effective when information that is too complex is included in the image. Therefore there is a need for alternative media to facilitate access to provide information on how to pay for the public and facilitate the payment process to improve the performance of BPA in conducting promotions. Augmented Reality is an alternative media that was built to package information on payment methods in the form of 3D animation and produce narrative sounds. The method used is Markerless. With the user-defined target feature technique found in vuforia, users no longer need to print a marker to display digital elements. Based on the results of testing on testing the detection of test response time using the OPPO f1 smartphone is able to detect marker with a time of less than one second. The minimum distance in detection is poor if it is less than 5cm and more than 300cm, while the distance of a good marker is between 6-300cm. The minimum angle of detection of bad markers is 0˚, while the angle of detection of bad markers is 45˚ and 90˚.
Heritage languages in migration and Italian «lingua filiale» Some evidence from Friuli Venezia Giulia

The presence of students with a migration background in Friulian primary and middle schools is growing and it is characterized by an increasing degree of variability. More specifically, in recent years the incidence of pupils born in Italy to foreign parents has become higher, and this represents a new concern for the local educational institutions. Field data collected by Impact FVG 2018-20 researchers highlight some relevant sociolinguistic traits of this environment and raise new questions. The study of the speakers’ repertoires shows that the traditional L1 and L2 definitions can be applied less precisely than in the past, as new situations and blurred margins of uncertainty appear. This contribution introduces some relevant aspects emerged during the Impact FVG 2018-20 study, which suggest to consider under a new light both the condition of the heritage languages, and the domains in daily communication where Italian is extending its presence. This framework seems to invite schools to diversify their actions and to introduce new inclusive strategies, in order to sustain and promote these languages, which at the moment appear to be often connected to a migratory past, and less directly learnt by these young emerging bilingual speakers.
TINGKAT KEPUASAN MAHASISWA ATAS KINERJA DOSEN PADA PEMBELAJARAN ONLINE MASA PANDEMI COVID - 19 DI IIB DARMAJAYA

The purpose of this study was to investigate the level of student satisfaction with the performance of lecturers inOnline Learning during the Covid-19 Pandemic at IIB Darmajaya. This research is a quantitative research.Sources of data in this study using primary data. Data collection in this study used a questionnaire which wasdistributed to respondents. The population in this study were active students at IIB Darmajaya, amounting to 2575people. To determine the size of the sample, the researcher used the Slovin formula with a significance level of 10%and the number of samples obtained was 96.26 samples and rounded up to 100 respondents. The data analysismethod in this study uses descriptive analysis by calculating the average score in measuring lecturer performanceas a determinant of service quality applied in research institutions which consists of 7 dimensions, including:Performance (Appearance), Mastery of lecture material, learning process, Use of learning media, Learning withstudent involvement, Assessment of Learning Outcomes, Closing. The results show that students feel very satisfiedwith aspects of performance, learning process, use of learning media, learning by involving students, andassessment of learning outcomes. Meanwhile, aspects of mastery of lecture material and closing students feelsatisfied.
Using classification systems in e-catalogs, e-libraries and open archives

Key requirements to search interface in e-catalogs are generalized. Alternative initial search pages of e-catalogs and e-libraries are discussed. Causes for classification underuse for search are specified. Advantages of search with classification systems are substantiated. The paper is prepared under the State Order to RNPLS&amp;T No. 730000F.99.1.BV09AA00006 for 2021.
Subject Research, Course Guides, Documentation: Hyperlinked Stories with Twine: Changing the Styling

This guide introduces Twine as a lightweight and open-source tool to craft your own hyperlinked stories and games.
Secure Ramp Merging using Blockchain.

Connected vehicles nowadays can provide a variety of useful and advanced services to their owners, manufacturers, transportation authorities, and other mobility service providers. Securing the complex sensing and networking protocols that enable these applications is an important and difficult problem. In this paper, we use blockchain which is traditionally used in applications from cryptocurrencies to smart contracts, as a potential solution to CV security. Specifically, we exploit the immutability of blockchain to ensure safety from falsified information and attacks. We demonstrate these properties by developing an algorithm that uses blockchain to maintain trusted communications between vehicles in the context of a cooperative ramp merging application.
Computing Specification-Compliant Reachable Sets for Motion Planning of Automated Vehicles.

To safely and effectively participate in road traffic, automated vehicles should explicitly consider compliance with traffic rules and high-level specifications. We propose a method that can incorporate traffic and handcrafted rules expressed in time-labeled propositional logic into our reach ability analysis, which computes the over-approximative set of states reachable by vehicles. These reachable sets serve as low-level trajectory planning constraints to expedite the search for specification-compliant trajectories. Depending on the adopted specifications, related semantic labels are generated from predicates considering positions, velocities, accelerations, and general traffic situations. We exhibit the applicability of the proposed method with scenarios from the CommonRoad benchmark suite.
Target detection in haze background by applying polarimetric imaging dehazing method

Polarimetric imaging is a technology which collects the polarimetric information of targets and forms an image. It has been proven that polarimetric imaging method has unique advantages at the area of target detection in the haze, dust and other scattering medium background. In this paper, a new polarimetric dehazing method is proposed based on low-pass filtering techniques. A linear polarization camera is employed to grab images with four different polarization directions, and the low-pass filtering operation is applied to remove the high-frequency components which contain the information of noise and targets, which will improve the accuracy of estimation of airlight, and then the haze background and objects in these images can be separated based on the difference of their polarization characteristics. For the purpose of verifying the effectiveness of the proposed method, multiple groups of images of advertising boards and buildings have been grabbed and processed by this method, and the experimental results indicate that the presented scheme can reduce the adverse influence of haze and improve the visual range effectively.
Study of Potential Classification of Lost Students in College Based on Information Extraction on Text-Based Social Media; Case Study of Panca Budi Pembangunan University

The main problem studied in this study is the large number of lost students who harm universities because of the difficulty of monitoring or monitoring as a preventive measure. Therefore, this research becomes very important to be done so that college institutions can make efforts to detect early (classification) of students who potentially cannot complete their studies on time or students who will drop out (DO). Thus, PT institutions through related parties such as academic guidance lecturers, academic bureaus and others can do initial prevention by providing the best solution or solution to the problems faced by students. This research aims to determine the training data model consisting of academic and non-academic factors (including the results of extracting information from social media). Furthermore, this model is used as a basis for classifying students who have the potential to "graduate on time", "graduate not on time", and "DO". The method approach used is quantitative with text mining computational algorithms for the process of extracting knowledge / information from social media which is further used in data training, as well as data mining computational algorithms for the process of classification of potential completion of student studies. The mandatory external targeted in the first year is the publication of the international journal Scopus Q4 and in the second year is the publication of the international journal Scopus Q3. For additional external targets in the first and second years respectively are the publication of international journals indexed on reputable indexers, ISBN teaching books and copyrights. The level of technological readiness (TKT) in this study up to level 2 is the formulation of technological concepts and applications to classify the potential completion of student studies using data mining. Keywords: [student lost, knowledge/information extraction, data classification, text mining, data mining].
SCRAPING WEB MARKETPLACE MENGGUNAKAN METODE DOM PARSING UNTUK PENGUMPULAN DATA PRODUK

Web Scraper is a way of extracting scripts that run there that are commonly chosen to do web memos via DOM parsing. Specific nodes that are collected using DOM parsers and tools like XPath help the process of scraping web pages. In this study using the DOM Parsing method to obtain product data on the market. Sraper can be further developed as a data collection technique on the internet for further research that can be provided about the concept of big data to be used for forecasting or getting the information needed. Alone Parsing is a way of breaking data or symbols, both in language and in language, according to formal grammar rules. After using the parshing technique, it will be generated again using Parse Tree, which is a process of compiling product data that forms like a tree, using siyntak analysis to break down product categories.
Leveraging Motion and Conceptual Frameworks of Sound as a Novel Means of Sound Design in Extended Reality

Extended Reality (XR) technology presents a wealth of new opportunities and challenges to sound design. Whilst existing knowledge and best-practice can translate readily across, XR realises several specific features and qualities that warrant more focussed attention. This chapter makes the case for considering the potential of human motion, a central point of added value in the affordances of XR. Motion tracking in virtual, augmented and mixed-reality systems affords increasingly naturalistic means of human-computer interaction but, crucially for sound designers, also presents a wealth of prospects for designing sound within XR that draws deeper connection between the user and the system.
Novel Nanosurfactants and their Industrial Applications

Nowadays, nanotechnology has revolutionized many scientific fields of health, consumer products, drugs, personal care, food industry, packaging and agriculture industry and focuses on the constructiveness of the products and stability of formulations. Nanotechnology manipulates the world at molecular and atomic levels due to its characteristic features. In nanotechnology, surfactants have a wide range of applications. Surfactants have been a decisive subject of analysis since the beginning of life. It is used widely as nanoparticles because of its high outcome on dispersion. Owing to this, they are found to be used in diverse industrial application, such as personal and health care, agrochemicals and cosmetics etc., of nanotechnology. Recently, nanosurfactants are under investigation in many scientific fields. Nanosurfactants are the materials which avoid the agglomeration of small dispersed nanoparticles within the solution and offer a very high surface area having a widespread application for water and soil pollution treatment. All these applications and future directions, for the use of nanosurfactants in nanotechnology, are discussed in light of recent discoveries and developments.
Revisiting Multi-Codebook Quantization

Multi-Codebook Quantization (MCQ) is a generalized version of existing codebook-based quantizations for Approximate Nearest Neighbor (ANN) search. Specifically, MCQ picks one codeword for each sub-codebook independently and takes the sum of picked codewords to approximate the original vector. The objective function involves no constraints, therefore, MCQ theoretically has the potential to achieve the best performance because solutions of other codebook-based quantization methods are all covered by MCQ's solution space under the same codebook size setting. However, finding the optimal solution to MCQ is proved to be NP-hard due to its encoding process, i.e., converting an input vector to a binary code. To tackle this, researchers apply constraints to it to find near-optimal solutions or employ heuristic algorithms that are still time-consuming for encoding. Different from previous approaches, this paper takes the first attempt to find a deep solution to MCQ. The encoding network is designed to be as simple as possible, so the very complex encoding problem becomes simply a feed-forward. Compared with other methods on three datasets, our method shows state-of-the-art performance. Notably, our method is 11×-38× faster than heuristic algorithms for encoding, which makes it more practical for the real scenery of large-scale retrieval. Our code is publicly available: https://github.com/DeepMCQ/DeepQ.
SiPOS: A Benchmark Dataset for Sindhi Part-of-Speech Tagging

In this paper, we introduce the SiPOS dataset for part-of-speech tagging in the low-resource Sindhi language with quality baselines. The dataset consists of more than 293K tokens annotated with sixteen universal part-of-speech categories. Two experienced native annotators annotated the SiPOS using the Doccano text annotation tool with an inter-annotation agreement of 0.872. We exploit the conditional random field, the popular bidirectional long-short-term memory neural model, and self-attention mechanism with various settings to evaluate the proposed dataset. Besides pre-trained GloVe and fastText representation, the character-level representations are incorporated to extract character-level information using the bidirectional long-short-term memory encoder. The high accuracy of 96.25% is achieved with the task-specific joint word-level and character-level representations. The SiPOS dataset is likely to be a significant resource for the low-resource Sindhi language.
Khan Academy y el aprendizaje matemático en estudiantes de básica superior

The objective was to determine the effectiveness of the Khan Academy platform in the mathematical learning of the students of upper basic. Explanatory research with a quasi-experimental group design. The Khan Academy platform is a tool that improves the acquisition of significant learning, since according to the results obtained from 27 tenth grade students of Basic General Education, a pre-test was applied in the multiplication of real numbers, presenting an average of 1.4815, and Then a post test was applied, increasing the average 2.8519, after having worked on the platform, there was a significant change and as a consequence increased academic performance. The Khan Academy digital platform, through interactive videos, allows students to have direct contact with the study material.