Reviewerly/exHarmony huggingface dataset:
The Analysis of Gerunds in The Adventure of Sherlock Holmes

Abstract. This research aims are to identify the uses of gerunds found in The Adventure of Sherlock Holmes and to describe their application in teaching reading. It belongs to qualitative research. The researchers used a collection of short stories by Arthur Conan Doyle entitled The Adventure of Sherlock Holmes as the data source. The researchers then identified the sentences containing gerund, classified the gerund found in the short story based on its use, counted the percentage of the gerunds, discussed the finding of the analysis, applied the result of finding in teaching reading, and drew conclusion and suggestion. In conclusion, there are 2 gerunds as subject (0.71%), 13 gerunds as direct object (4.59%), and 268 gerunds as object of preposition (94.70%) and they can be applied in teaching reading for the twelfth-grade students of Language Program of senior high school.
BOOS : AN ANDROID APPLICATION ON LEARNING KADAZANDUSUNLANGUAGE FOR NON-NATIVE KADAZANDUSUN SPEAKERS

Language learning using mobile application become a revolution for a learning platform as more people nowadays turns to smartphone and tablet. As there are numerous language learning mobile apps that have been developed, it indicates that language can now be learnedby all people from different backgrounds and ages. Hence, an Android application on learning KadazanDusun language is introduced as a learning platform to respond to the new technology since there is no KadazanDusun learning platform using Android technology that provided for non-native KadazanDusun speakers. Boos as the name of the language learning application has developed to aid the learners to learn KadazanDusun language in interactiveway. This application would be useful and provides effective learning to the learner.
Self-learning Tags and Hybrid Responses for Deep Knowledge Tracing

Knowledge Tracing, as a classic task of evaluating student knowledge mastery and predicting performance by modeling student response sequences, has become one of the key motivations for stimulating the vigorous development of personalized online education. With the support of Recurrent Neural Network, Deep Knowledge Tracing (DKT) and its variants demonstrate remarkable KT performance on account of their excellent learning ability and knowledge state representation. However, the drawbacks of these models have gradually emerged with the surge in student interaction data scale and the variety of interaction forms, which include employing the pre-defined knowledge point tags and the single response feature input. In this paper, we advocate a brand-new LTDKT-HR model, which constructs exercise embedding mapped from exercise space to tag space by self-training and optimizes input by adding an effective feature of first response time to the original feature of whether answer is correct or not. Sufficient experiments on two open datasets prove that LTDKT-HR outperforms the general DKT in student performance prediction, that is, self-learning tags are superior to existing manual tags. In addition, the proposed model can dig out the influence between exercises, which provides the mathematical basis for further setting exercise relationship constraints.
Syllables and Stress in Uzbek Nouns and Adjectives: With a Comparison to English and North Kyungsang Korean

This research analyses the syllables and stress placement in Uzbek nouns and adjectives. Syllables in Uzbek are divided into heavy and light to explain quantity-sensitivity in stress placement: Heavy syllables tend to attract stress. Previous studies argued that in Uzbek, stress docks on the final syllable except for loan words. However, this rule encounters exceptions. Hence, we have come up with new stress rules. Uzbek nouns and adjectives are stressed on the rightmost heavy syllable which is usually, but not always, a final syllable. In addition, if words do not contain any heavy syllables, then stress falls on the final light syllable. Furthermore, with the morpho-phonologically made superlative degree adjectives, stress falls on the word-initial heavy syllable. Finally, we will make a three-way comparison between the Uzbek stress system, the English stress system, and the North Kyungsang Korean tonal system, identifying the similarities and differences among them.
Optimizing the Profit of an Agricultural Company through the Application of Genetic Algorithms

For the proper planning of production processes in agricultural companies, resources are needed that allow the development of methodologies capable of bringing optimal solutions that support decision making.The aim of this study was develop a prototype to optimize the profit of an agricultural company through the application of genetic algorithms.Obtaining data regarding production processes belong to a dairy company specialized in the manufacture of dairy products, located in the municipality of Caruaru, state of Pernambuco.An on-site visit was carried out to survey the entire production process of the products under study; interview with the business owner to learn about their main market interests; collection of data for the elaboration of a business model, with emphasis on product diversification and improvement in the company's profit margin.From the data, an "AG planning" prototype was developed using the python language and the tkinter library.For the implementation, the objective based function was first developed.in profits and 10 restrictions were modeled based on manufacturing time of each product, number of employees and hours worked.Three repetitions of 3, 6 and 10 executions of the algorithm were performed to verify the highest possible profit value.The most significant increase in the profit margin was identified infirst simulation with 3 runs.With the using genetic algorithms it was possible to plan the weekly production of the company.
Penerapan Vector Space Model Dalam Klasifikasi Penilaian Thematic Appeception Test

Psychology is the study of human mental behavior and functions scientifically. In practice, a person's personality can be assessed from psychological tests. One of the psychological tests is the Thematic Apperception Test (TAT). TAT Test is a projective psychological test consisting of various themes presented in the form of an image which is then projected accordingly with the response. The purpose of the TAT is to reveal the dynamics of the subject's personality in the form of encouragement, sediment, complex, and various dominant conflicts. Thematic Apperception Test still uses a card and tape recorder to record Testee's voice. Calculation of results or assessments is still done manually. Errors in the assessment will affect the results, so we need an intelligent information system using the vector space model method based on experience in the field of psychology. A web-based system which can provide personality test results and information about the Thematic Apperception Test. From the test results using 10 stories, it was found that the average precission value was 72.7%, the average recall value was 86.7%, and the average f-measure value was 78.3%.
TEKNIK PENYUTRADARAAN PADA DOKUMENTER “MAKAN DARI TINJA” SEBAGAI PELUANG BISNIS YANG MENGUNTUNGKAN

Suction toilet or suction feces is a business engaged in services. Not many people know that this This business is cultivated by Muhayar as a suction business toilet, for 20 years Muhayar has been in the business to develop.The method used in making this film through the stages of determining the theme, research, determining the story, making a production schedule and determining the work tools at the preproduction stage, taking pictures at the production stage, as well as editing the production at the post-production stage.The directing technique in the documentary ate from feces as a lucrative business opportunity into a film consisting of 3 segments put together, with a duration of 21 minutes. Each segment is presented directly by the resource person along with the picture documentation. This film puts forward directing techniques, especially angle cameras, in making this work. This documentary focuses on the figure of Muhayar as a suction entrepreneur. With the power of the concept of the designer of the work presenting different documentary films, with the hope that audiences who see entertained and get useful information.
The Main Issues on Keyword Retrieval from Audio Streams

In recent years, with the rapid development of speech recognition technology, voice interfaces on intelligent devices have been increasing very popular, such as Google Voice Search. Intelligent speaker and mobile assistant, etc. These are different Smart devices give users a completely hands-free experience. Start by listening to specific keywords Voice input. Keyword recognition (KWS) or keyword detection is a task designed to detect predefined keywords in a stream of audio. This paper mainly introduces some advanced technologies for speech keyword retrieval.
Balance the Labels: Hierarchical Label Structured Network for Dialogue Act Recognition

Existing works for Dialogue Act Recognition (DAR) pay little attention to the imbalanced distribution of the Dialogue Acts (DAs) and exclusively train their models over very fine-grained DAs in one pass, which leads to a limited performance in recognizing low-frequent DAs. To address this issue, we propose a hierarchical label structured network that explicitly introduces coarse-grained DAs to the original fine-grained DAs. A two-pass multi-head attention mechanism is devised to integrate different levels of DA information into the utterance encoding process, thereby utilizing the information learned from the coarse-grained DAs to guide the recognition of the target fine-grained DAs. Besides, a transfer learning over large-scale dialogue datasets is also employed to further boost label representation of the coarse-grained DAs. Extensive experiments show that our model significantly outperforms the state-of-the-art methods, verifying the effectiveness of integrating the hierarchical structure among DAs.
Hierarchical Reduced-space Drift Detection Framework for Multivariate Supervised Data Streams

In a streaming environment, the characteristics of the data themselves and their relationship with the labels may change over time.Most drift detection methods for supervised data streams are performance-based, that is, they detect changes only after the classification accuracy deteriorates.This may not be sufficient in many application areas where the reason behind a drift is also important.Another category of drift detectors are data distribution-based detectors.Although they can detect some drifts within the input space, changes affecting only the labelling mechanism cannot be identified.Furthermore, little work is available on drift detection for high-dimensional data streams.In this paper we propose an advanced Hierarchical Reduced-space Drift Detection (HRDD) framework for supervised data streams which captures drifts regardless of their effects on classification performance.This framework suggests monitoring both marginal and class-conditional distributions within a lower-dimensional space specifically relevant to the assigned classification task.Experimental comparisons have demonstrated that HRDD not only achieves high-quality performance on high-dimensional data streams, but also outperforms its competitors in terms of detection recall, precision and F-measure across a wide range of different concept drift types including subtle drifts.
LibGuides: Computer Skills: Blackboard Skills

This brief tutorial guide leads you to ways to brush up on your computer skills. It is useful for new students or students who may need some basic skills training.
HEALTH EDUCATION ON ACUTE RESPIRATORY SYNDROME AND URIC ACID TESTING FOR COMMUNITY IN GUNUNGSARI DISTRICT, PEMIJAHAN, BOGOR COUNTY

Efforts to prevent acute respiratory infections (ARI) are very important, because of the ease of transmission and can cause death. Health data from the Desa Gunung Sari Health Center, Kecamatan Pamijahan, Kabupaten Bogor in 2017 indicated that ARI was the most frequent complaint. The purpose of this community service is to educate health cadres about ARI. In addition, an examination of uric acid levels was held for the people of Desa Gunung Sari which was a series of counseling activities. The method used is counseling and direct examination. The counseling participants were 45 people and the uric acid examination was 146 people. The results showed that the cadres listened well to the counseling material, as seen in the correct answers to spontaneous questions during the counseling. The community's uric acid levels were mostly in the normal category and education helps increase public understanding of ARI. Thus, the continuity of similar activities is very much needed.
Digital Education and Information Security in Obstetric Students in COVID-19 Pandemic Times in Peru

The objective was to determine the relationship between the digital education topics addressed during the learning of obstetric students and the perception of the security of their information during the virtual education developed because of COVID-19 at the Santiago Antúnez of Mayolo National University (UNASAM) (Huaraz-Peru). It was a cross-sectional research carried out with 179 students, using a previously validated online questionnaire. The SPSS program and the Chi square test (p < 0.05) were used. The majority of obstetric students (64.8%) denied having developed the digital education topics consulted during the virtual learning sessions, mainly in the establishment of secure keys (83.8%) and the protection of confidentiality (82.7%); also evidencing a majority perception of insecurity regarding the safeguarding of their academic information on the Internet. It was concluded that there is a statistically significant relationship between the insufficient explanation of digital education topics during the learning of obstetric students and the high perception of insecurity of their information during virtual education developed because of COVID-19.
Invoice Smart Contracts for Design SMEs

In recent years, Blockchain technology has evolved from its original application in cryptocurrency and can now be used for applications such as Smart Contracts. Smart Contracts automatically Execute transactions without the need for a central authority however there are very few use cases of the technology, particularly amongst UK AEC Design SMEs. This paper uses a hybrid method approach which combines questionnaires with semi-structured interviews to create a framework which showcases how a Smart Contract invoicing process could work for Design SMEs. This could create an automated invoicing process which is more efficient and reduces the risk of late payment.
Virtual mentoring of young foreign language teachers in the organization of extracurricular activities

Modern students belonging to generations A and Z cannot imagine their life without the virtual world, so there is a need to use innovative approaches to organizing lessons and extracurricular activities in foreign languages. Digital technology plays an important role in this process, but not all teachers can quickly adapt to work in the new format. The issue is especially relevant for beginning foreign language teachers who do not have sufficient experience to effectively organize extracurricular work as an integral form of teaching foreign languages. This paper aims to consider virtual mentoring as a form of adaptation of teachers to modern digital technologies for organizing extracurricular activities of students belonging to generations A and Z. The analysis of scientific and methodological literature on this topic allowed the authors to identify a description of particular cases of the use of digital educational systems in teaching various aspects of a foreign language in the classroom and the need for the formation of digital literacy of the student. The paper clarifies how extracurricular activities can improve the students’ progress in a foreign language, proposes a form of virtual mentoring as a modern and convenient model of interaction that can increase the virtual competence of foreign language teachers, highlights and describes the features of children of generation A and Z, based on the study of which it was established the need to introduce a large number of digital technologies and the transition to a distance learning format when organizing extracurricular activities.
Basic bounds on cluster error using distortion-rate

Clustering is a popular type of unsupervised learning technique that performs natural groupings on samples to generate probably approximately correct groups. These clusters or groups are expected to have high intra-similarity and high inter-distinctiveness. Practical clustering problems may combine varying levels of intra-similarity or quality and distinctiveness or diversity. We propose an information analytic approach to measure the quality and diversity given in terms of the cluster error. Unlike previous models that show information measures derived from probability of samples in cluster, the proposed framework employs distortion-rate approach by first formulating the probability of distortion for multiple-types of samples in the cluster. In this framework, cluster formation is shown as naturally greedy action which leads to showing the average minimum distortion of cluster. We also obtain probabilistic bounds on the cluster error and present case study on use of distortion-rate approach for clustering. For limiting case of binary typical cluster, the bound is shown to resemble Fano inequality. For the first time, analytic performance limits along with notion of bias and variance are formalized for clustering.
PENGARUH PENERAPAN MODEL PROBLEM BASED LEARNING DAN MOTIVASI BERPRESTASI TERHADAP HASIL BELAJAR SISWA KELAS V DALAM MATA PELAJARAN MATEMATIKA

This study aims to determine the effect of applying Problem Based Learning model and achievement motivation on the learning outcomes of fifth grade students. The research method used in this study is a quantitative method with two-variant analysis techniques. This type of research is experimental research. The subjects of this study were the fifth grade students fo SDN Jemundo 1, totaling 25 students as the experimental group and the fifth grade students of SDN Sadang, totaling 24 students as the control group in the 2020/2021 school year. The results of this study are (1) there is an effect of applying Problem Based Learning (PBL) model (mean of 81.24) and conventional learning (mean of 79.20) on the Mathematics subject of fifth grade students of SDN Taman sub-district Sidoarjo where PBL model is more effective with a significance value of 0.000. (2) there is an influence of achievement motivation on learning outcomes where students with high achievement motivation (mean value 81.46) are superior to students with low achievement motivation (mean value 78.63) with a significance value of 0.001. (3) there is an interaction between the application of PBL model and achievement motivation on learning outcomes with a significance value of 0.001. Thus, problem based learning model and achievement motivation can effect student leaning outcomes in mathematics. &#x0D; Keywords: Problem Based Learning (PBL) model, Achievement Motivation, Outcome of Learning
Identification of Classroom Behaviors among the School going Children with a view to Develop a Guideline on Management of Indiscipline Behaviors

Context:  Disruptive classroom behavior leads to loss of curriculum time and creates a classroom environment that is not conducive to learning. Teachers face immense problem in dealing with such issues and are in constant dilemma on how to tackle the behavior of students in classroom.  Aim:  The present study was conducted to identify the classroom behaviors of school going children’s and to develop a standard guideline on management of indiscipline classroom behavior for teachers.  Materials and Methods:  A cross-sectional descriptive study was conducted among 100 school going children studying in school of Kolkata, India during 2016. Participants were recruited via quota sampling technique. Data was collected using self-structured and validated tools consisting of Tool I- Socio-demographic information and Tool II-Checklist for classroom behavior. Statistical analysis was done using SPSS version 18.  Results:  On assessment, majority of the students acquired discipline behavior (51%) followed by indiscipline behavior (49%). Classroom behavior of the students were found to be significantly associated with the educational standard and number of siblings of the students at p<0.05 level of significance. In view of the results, a guideline was formulated and validated for the management of indiscipline behavior among students.  Conclusion:  Students were almost equally distributed among the two variants i.e. possessing discipline and indiscipline behavior which demands the need of developing a discipline guideline for teaching the students.
Robust and Fast Excitation Fluctuations Transfer between Two Membranes in an Optomechanical System

The quantum state control or entanglement preparation for macroscopic matter is an attractive research. Optomechanical system provides an ideal platform to observe the quantum behaviors of macroscopic matter. In this paper, we present a scheme to implement the average excitation fluctuations transfer between two membranes in an optomechanical system via shortcut to adiabatic passage which is based on transitionless quantum driving. In order to quickly attain the transfer, we choose a suitable evolution path and optimize the experimental parameters. Numerical simulation demonstrates that the proposed scheme is robust against membrane damping and cavity decay. Furthermore, this idea can be used to generate entanglement of two membrane modes in a short time. Finally, we also discuss the experimental implementation of this scheme. This work may provide a new method for generating the macroscopic superposition state in the optomechanicalsystem.
The Technique of English Word Syllable Division in Speech Synthesis Based on Neural Network

With the increasing maturity of speech synthesis technology, on the one hand, it has been more and more widely used in people’s lives; on the other hand, it also brings more and more convenience to people. The requirements for speech synthesis systems are getting higher and higher. Therefore, advanced technology is used to improve and update the accent recognition system. This paper mainly introduces the word stress annotation technology combined with neural network speech synthesis technology. In Chinese speech synthesis, prosodic structure prediction has a great influence on naturalness. The purpose of this paper is to accurately predict the prosodic structure, which has become an important problem to be solved in speech synthesis. Experimental data show that the average error of samples in the network training process is lel/85, and the minimum value of the training error after 500 steps is 0.00013127, so the final sample average error is lel = 85 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>∗</mi> </math> 0.0013127 = 0.112 &lt; 0.5, and use the deep neural network (DNN) to train different parameters to obtain the conversion model, and then synthesize these conversion models, and finally achieve the effect of improving the synthesized sound quality.