Reviewerly/exHarmony huggingface dataset:
Relevance factors of mathematical education for sustainable development

Education system is viewed as an important constituent of sustainable development of a society. The spread of information technology reduces the need for mastering the computing apparatus of mathematics. On the other hand, firstly, the role of mathematics is not limited at least to its computing apparatus, the other components of the mathematical apparatus (for example, conceptual, methodological, etc.) and other aspects of mathematics (historical, activity, education of “intellectual honesty”, the formation of specific types of thinking, for example, geometric, ampect, linked with modelling, etc.) are also significant issues; secondly, the use of a computing apparatus is actually the final stage of other types of mathematical and “near-mathematical” activities. The article identifies three factors that ensure the relevance of mathematical education for the sustainable development: 1) the system of teaching mathematics should form the ability to use the mathematical apparatus for solving problems of business, management, engineering, social development, etc. (five components of this factor are highlighted); 2) focus on working with educational material at the level of typical strategies and methodology, not limited to typical algorithms; 3) presentation of mathematics as a multidimensional cultural phenomenon, in which scientific, technical, aesthetic, historical and economic as well as historical and social aspects are distinguished (this in many cases requires the processing of the teaching methods constituents, in particular, curricula alongside with the educational and methodological support).
LibGuides: Digital Citizenship: Resources

List of Tools and Tips to not only assist you in becoming the best student you can be, but also the best 21st Century Learner! With the continued use of Social Media and other digital communication networks, it is important for us to all realize we are no
Blockchain for Real Estate Industry

Blockchain technology is one of the latest technologies on the horizon and has evolved over the last 7-10 years. There is tremendous potential for usage of Blockchain technology in todayâ€™s Real Estate industry. This paper aims to analyze the disruptive power of Blockchain digital technologies in the real estate industry. This paper will start with an introduction of the blockchain technology and high-level technical overview. It will then go on to discuss the various benefits the Real Estate industry can reap from this technology. It will also put forth various use cases or opportunities in the Real Estate sector for this technology. In the end, the paper will also discuss the present-day limitations and the questions marks over this technology in relation to its usage for the Real Estate industry.
Foggy Image Detection and Filtration Methods: Review

Image de-fogging in brightness defined to image calculated in a deprived climate like as fog, rain and ocean and pollutants or dust particles. To alter the fog and some other pollutants from the image, various methods are customized, some mainly utilized methods are DCP, Detection, and Classification of foggy images. Haze is an arrangement of dual components, air-light and DA (Direct Attenuation), low image quality and generates various issues in VS (Video Surveillance), Navigation and Target Tracking, etc. So, its removes from an image, several de-fogging approaches have been discussed in this paper. Image De-fogging can attain utilizing several and single image haze removal techniques. The famous methods are discussed in this paper used for image de-fogging in DCP, Depth-map for accurate estimation, Guided Filter, and Transmission methods. These techniques still efficient in removing haze from images have very high time complexity. The guided filter is a new region preservative filter with region enhancement and smoothing. The previous result was a local linear transformation of the Guided Image. It defines a review of the classification and detection technique of a hazy image. This method mitigates the limitations of filtration and DCP and at the same time preserves the image quality. At that time, described the existing image de-fogging methods containing image restoration, contrast improvement, and fusion-based image de-fogging methods.
Performance Evaluation of BERT Vectors on Natural Language Inference Models

Natural language inference aims to classify the binary relation between opinionated sentences as a contradiction, entailment, or neutral. To accomplish the task, classifiers transform textual data into numerical representations called vectors or embeddings. In this study, both static (Glove, OntoNotes5) and contextual (BERT) word embedding methods are used. Classifying the logical relationships between opinionated sentences is difficult. These sentences have complex grammatical structures to convert them into logical representations, and traditional natural language processing solutions are insufficient to meet the requirement. This study uses Decomposable Attention and Advanced LSTM for Natural Language Inference (ESIM) deep learning methods to perform this classification. The best accuracy score is achieved with 88% using ESIM - BERT on the SNLI corpus.
Emoji's multi-interpretation effect on the intended emotion

There are some questions that are still unanswered about how certain emojis can be used to send the intended message accurately, such as the effect of intentions, perceptions and feelings. The positive effect of positive oral messages is increased by emotions, like shouting or speaking slowly, but emojis may send positive messages which contradict the outcome of certain intended ideas about the message. Therefore, this study investigates whether emoji increase the relationship between the use of direct mood-specific emojis and indirect mood-specific emojis intended interpretation. Experimental analysis on focus group approach with emoji from two mobile messaging applications was conducted with 30 participants divided into control group and alerted group in different experimental sessions. The analysis of the findings indicates that most emoji use are suitable for expressing emotional sensations, but they do not create a time limit to which the emotions get associated with the sign. In addition, the interpretation of communication with multiple emoji in each experimental group interaction was significant, but emoji fail to express the impact on neutral and negative messages to a large degree. Hence, this study contributed to an understanding of the influence of multiple emoji interpretations on the intentionally evoked emotion
Elements Of Humor In Teaching

Studies Related To The Element Of Humor In Teaching In Malaysia Are Getting More Attention Even Though The Level Of Implementation Is Relatively Low. Liao Y, Luo S, Tsai M (2020), An Exploration Of The Relationships Between Elementary School Teachers Humor Styles And Their Emotional Labor Stated That Humor Can Promote The Professional Development Of Teachers To Build Appropriate Programs In The Work Environment. The Findings Of The Study Showed That 95 % Stated That The Element Of Humor Can Increase The Concern And Needs Of Teachers In Working. Thus, The Practice Of The Element Of Humor Among Teachers Should Be Applied In Teaching And Learning In The Classroom.
Image Processing: Human Facial Expression Identification using Convolutional Neural Networks

Facial expressions identification is the growing area of interest as it attracts the advancement in technology by focusing on human computer interaction. Many researchers has got their hands on various approaches for automatically generating the expressions of human faces. Emotions and expressions are inter relatable where expressions are facial movement for expressing the emotions of human being. Image processing is the technology which helps in identifying expressions by including factors such as the face detection, the feature extraction and the expressions classification. Two datasets FER-2013 and CK+48 are used in the process of identifying the expressions like sad, fear, happy, angry, surprise, neutral, disgust, contempt.  HAAR features based adaboost cascades are used to identify the features of a face which helps in detecting facial points and makes it easy for further process of expression detection. The deep learning technique, convolutional neural network (CNN) is implemented for classification of expressions for prediction
CLOUD SERVER DALAM PEMBUATAN APLIKASI FOTOBLOG REALTIME BERBASIS ANDROID

Today in the development of technology, the process of sharing photos gradually begins to develop. Where individuals who want to share photos need media to be able to share photos that are considered interesting. At present many social media can be used to share interesting photos but as students generally do not know the processes that occur in building a social media application sharing photos. Like how to build an application using a database system that is online so that it can be accessed by many people using an internet connection. To build an application that has a database so that it can be used online, a cloud server is needed, a technology service that combines computers and internet-based networks. So this technology utilizes internet media as a central server for data management. At this time Google has provided a cloud server service called Firebase.
ENHANCING STUDENTS’ ABILITY IN SOCIOLINGUISTICS DURING THE COVID-19 PANDEMIC THROUGH ONLINE STAD–TYPE COOPERATIVE LEARNING MODEL

This research was initiated by the lecturers’ difficulties in presenting fun learning during the Covid-19 pandemic. This study aimed to determine the improvement of students' abilities in learning Sociolinguistics during the Covid-19 pandemic by applying STAD Type Cooperative Model implemented through the Breakoutroom Zoom Application. This application facilitated lecturers to divide students in one class into small or large groups and they could still monitor the progress of the discussion. Utilizing Student Team Achievement Division (STAD) model in the Breakoutroom Zoom application aimed to achieve a good learning process. This research was a Classroom Action Research conducted in two cycles: Cycle I and Cycle II. This research was carried out in four stages: planning, acting, observing, and reflecting. The object of this research was the sociolinguistics learning and the research subjects were the fourth semester students of Indonesian Language and Literature Education at the Faculty of Education, Hasyim Asy'ari University. There were 16 students consistinf of 4 male and 12 female students. The data were calculated quantitatively and analyzed qualitatively. Based on the results of the research, it was found that there was an increase in the Sociolinguistic learning after implementing STAD type cooperative learning model which was carried out online through the Breakoutroom Zoom application in cycle I and II. The increase was marked by an increase of the students’ score obtained in each cycle.
Teacher’s Questioning in Classroom Interaction towards Students’ Learning Process in an EFL Classroom

In the classroom, teacher‟s questions contribute an essential role in the students‟ learning process. In this study, the researcher aimed to investigate the types of teacher‟s questions conducted by the English teacher in the teaching and learning process and their roles towards students‟ learning process. This research is a qualitative study. The data of this research were collected through classroom observations, interviews, and audio-visual material. The participant of this research were grade X students of three classes at one of Senior High School in Surakarta. The research findings showed that: firstly, there were three types of teacher‟s questions conducted by the English teacher in the classroom. The questions were procedural, convergent, and divergent questions. Secondly, every question has each role in students‟ learning process. Procedural questions were essential to stimulate and maintain students‟ interest and motivation, check students‟ preparation, task, seatwork arrangement, and check students‟ understanding. The convergent question, on the other hand, were beneficial to encourage students‟ participation in a lesson, encourage students to think and focus on the content of the lesson and help the students to review and summarize the previous lesson. Lastly, divergent questions have a role in developing students‟ participation in a lesson.
Application for Donation Centers

The aim of this application was to look at how donations work and the way small-NGOs are adapting in terms of technology and also the growing crisis around Covid-19 and the way it's affected them adversely. The cross-platform application can facilitate NGOs to publish their desires and what has to be provided to the poor on pressing basis and also the donor will simply select based on their ability to present food, garments or commodities that they will present to those in want. The manual posts can facilitate the users select what they need to present rather than restricted selections. the appliance would be a linking bridge between unaware donors and NGOs searching for bound donors that may profit the necessitous.
Awareness Levels of Kenya Library and Information Service Consortium's (Klisc) Services and Resources at University of Nairobi and Kenya National Library Services

Kenya Library and Information Service Consortium (KLISC) has done outstanding activities such as shared acquisition and ICT trainings of librarians to support information service providers in Kenya. Kenya has over 600 institutions but only 123 are KLISC members, irrespective of their memberships, their subscribed information resources remain under-utilized. The study therefore tried to interrogate the awareness levels of the KLISC’s information resources and services by the users of member institutions. The purpose of the study was therefore to establish awareness levels of KLISC services and resources by users of KLISC member libraries. The study was conducted in University of Nairobi, KLISC headquarters and Kenya National Library Services (KNLS), Nairobi headquarters. The study used descriptive survey. The target population was KLISC’s member libraries in Nairobi County. Purposive sampling and stratified sampling techniques were used to obtain a representative sample size. Data were collected using interviews and questionnaires and analysed using Microsoft excel and narrative method. The study discovered that most respondents were only aware of the multi-disciplinary databases. Majority of them used the KLISC’s resources and stated the need for training on the access, use and search within these databases. The study concluded that majority of the library users were aware of the KLISC’s resources and consulted them alongside other sources. The study recommended that rigorous trainings on use and access to KLISC’s resources should be done regularly. The study also recommended that libraries should create awareness of all the KLISC’s information resources for full utilization of these resources.
Gradient-based Optimization for Multi-resource Spatial Coverage Problems

Resource allocation for coverage of geographical spaces is a challenging problem in robotics, sensor networks and security domains. Conventional solution approaches either: (a) rely on exploiting spatio-temporal structure of specific coverage problems, or (b) use genetic algorithms when targeting general coverage problems where no special exploitable structure exists. In this work, we propose the coverage gradient theorem, which provides a gradient estimator for a broad class of spatial coverage objectives using a combination of Newton-Leibniz theorem and implicit boundary differentiation. We also propose a tractable framework to approximate the coverage objectives and their gradients using spatial discretization and empirically demonstrate the efficacy of our framework on multi-resource spatial coverage problems.
Proof Net Structure for Neural Lambek Categorial Parsing

In this paper, we present the first statistical parser for Lambek categorial grammar (LCG), a grammatical formalism for which the graphical proof method known as proof nets is applicable.Our parser incorporates proof net structure and constraints into a system based on selfattention networks via novel model elements.Our experiments on an English LCG corpus show that incorporating term graph structure is helpful to the model, improving both parsing accuracy and coverage.Moreover, we derive novel loss functions by expressing proof net constraints as differentiable functions of our model output, enabling us to train our parser without ground-truth derivations.
Квантовые свойства психики и безэнтропийность процессов мышления

Participation of a superfluid condensate from light fermi-particles (levions) in biological and mental processes is considered. It is shown that reduction of entropy of such condensate as the structure co-operating with biomolecules of alive organism, reduces the general entropy of the biological system. The aspects of the mental processes with zero entropy and their connection with the theory of quantum measurements are considered.
STUDENTS’ PERSPECTIVES OF SIMON SAYS GAME TO PRACTICE LISTENING SKILL AT GRADE EIGHT STUDENTS OF MTSS MADINATUSSALAM IN 2020/2021 ACADEMIC YEAR

This research was aimed to find out students’ perspective of Simon Says game for practicing their listening class. The subject of this research was grade VIII-3 students at MTsS Madinatussalam in 2020 academic year. This research of this study was conducted by using qualitative research. The data used in this research such as; questionnaire, interview sheet and photography evidence. The questionnaire in this research consists of six questions that related to Students’ perspective of Simon Says game for practicing their listening. The researcher distributed questionnaire for twenty five students in grade VIII-3 of MTsS Madinatussalam’s students. The researcher also did interview for some students. The researcher gives six questions too in interview session to students that still related to students’ perspectives of Simon Says game for practicing their listening. The result of this research showed that almost all students have positive perspectives in Simon says game for practicing their listening. They agree that Simon Says game makes them easier to practice their listening in a fun way. They also agree that Simon says game can make their class atmospheres’ be active. They said they are being attractive while playing this game for listening practice class. Keywords: Simon Says game, Students’ Perspective, Listening Practice
SzegedAI at SemEval-2021 Task 2: Zero-shot Approach for Multilingual and Cross-lingual Word-in-Context Disambiguation

In this paper, we introduce our system that we participated with at the multilingual and cross-lingual word-in-context disambiguation SemEval 2021 shared task.In our experiments, we investigated the possibility of using an allwords fine-grained word sense disambiguation system trained purely on sense-annotated data in English and draw predictions on the semantic equivalence of words in context based on the similarity of the ranked lists of the (English) WordNet synsets returned for the target words decisions had to be made for.We overcame the multi,-and cross-lingual aspects of the shared task by applying a multilingual transformer for encoding the texts written in either Arabic, English, French, Russian and Chinese.While our results lag behind top scoring submissions, it has the benefit that it not only provides a binary prediction whether two words in their context have the same meaning, but also provides a more tangible output in the form of a ranked list of (English) WordNet synsets irrespective of the language of the input texts.As our framework is designed to be as generic as possible, it can be applied as a baseline for basically any language (supported by the multilingual transformed architecture employed) even in the absence of any additional form of language specific training data.
Recognition of Minimal Pairs in (un)predictive Sentence Contexts in two Types of Noise

Author(s): van Os, Marjolein; Kray, Jutta; Demberg, Vera | Abstract: Top-down predictive processes and bottom-up auditory processes interact in speech comprehension. In background noise, the acoustic signal is degraded. This study investigated the interaction of these processes in a word recognition paradigm using high and low predictability sentences in two types of background noise and using phonetically controlled contrasts. Previous studies have reported false hearing, but have not provided insight into what phonetic features are most prone to false hearing. We here systematically explore this issue and find that plosives lead to increased false hearing compared to vowels. Furthermore, this study on German for the first time replicates the overall false hearing effect in young adults for a language other than English.
Crossover Approach utilizing Ant Colony Optimization (ACO) and Neural Network for Anonymization in Big Data

With the expansion of distributed computing environment, many learning problems now need to affect with distributed input data. Applying Machine Learning techniques to guard privacy is termed as Privacy aware Machine Learning which can be simply accomplished by first anonymizing a dataset before liberating it for the determination of data mining or knowledge extraction. To reinforce support in learning, it is significant to deal with the privacy concern of every data holder by extending the privacy preservation notion to original learning algorithms.  Hence, a hybrid algorithm variant that incorporates back propagation algorithm with Ant colony Optimization (ACO) in Map Reduce framework is proposed. The proposed work permits a neural network to be trained without demanding either party to reveal data to the opposite. Human background is applied via interactive Machine Learning to the method of anonymization; this is often done by eliciting human preferences for preserving some attribute values over others within the light of specific tasks. The effect of interactive learning within the sector of anonymization will greatly depend upon the experimental setup, like an appropriate choice of application field and selection of suitable test focuses. Further, human knowledge in proposed MapReduce computer cluster yield a measurably better classification result for big data application.  We offer complete correctness and security analysis of our algorithms. Our experiments show that proposed work results in significantly improved classification effects than a rigid automatic approach.
The Effectiveness of <i>Imagine</i> Technique on the Ability to Write Poetry Towards the Tenth Grade Students of SMA Negeri 2 Tungkal Jaya

The question that to be solved in this research, was there any effect of the imagine technique on the ability to write poetry towards the tenth grade students public of High School (SMA Negeri) 2 Tungkal Jaya?This research used an experimental method with a posttest design (final result) in the control and the experimental class.This study aims to determine and describe the effectiveness of the imagine technique in the ability to write towards the tenth grade students of SMA Negeri 2 Tungkal Jaya.The sample in this study were 29 students of class X IIS 2 as the control class and class X MIA 1 which consisted of 29 students as the experimental class.The data analysis technique used was the test data analysis technique.Based on the results of the study, it shows that there was an effect of imagine learning techniques on the ability to write poetry towards the tenth grade students of SMA Negeri 2 Tungkal Jaya, which was shown by the t-test value obtained of 5.708 with a level (000 > 0.05).Due to the significant level 0.18 > 0,05, thus Ho was rejected and Ha was accepted.