Reviewerly/exHarmony huggingface dataset:
Meningkatkan Kemampuan Menggosok Gigi melalui Media Audio Visual bagi Siswa Tunagrahita Ringan (Single Subject Research Kelas VI di SLB Al-Hidayah Padang)

This research begins with the problem in SLB Al-Hidayah Padang, a child with mild mentalretardet children. brushing toothbrush has not mastered skills. This is seen when Researchers do observations and found that children still do not understand how the steps and how to brush teeth correctly.This research used experimental approach, single subject research (SSR, with ABA design, a data analysis technique used graphic visual analysis. The subject of this research is a children with mild mental retardet children. The target behavior in this study is the child can perform steps to brush teeth properly. Measurement of variables by using the percentage of the number of items of grains of the instrument. The results Showed that children's skills in brushing teeth Increased. Seen at baseline condition (A1) the which is done four times observation percentage Obtained by the child is still low, at intervention condition (B) with eight times observation, the percentage Obtained by child increase is from the initial condition, at condition of baseline A2 conducted five observation times the percentage of correct tooth brushing measures increases from the initial ability. Based on the data Reviews These show that, the audio vicual brushing toothbrush can improve the skills of children with mild retardet children
MULTISUBJECT SUDENTS’ PROJECTS AS A FACTOR OF FLEXIBLE COMPETENCE DEVELOPMENT IN STUDENTS OF AGRICULTURAL QUALIFICATIONS

The article is devoted to the urgent problem of the pedagogical search for the development of soft skills and self-control among students of agricultural sectors. The pedagogy of instrumentalism was chosen as a discursive basis and justification of the appropriateness of the application of project work technologies as an element of the development of self-awareness and self-determination in a dynamically developing post-industrial society. The experience of developing project activities at the university is compared with the practice of full-time education in the field of primary and general education. The case of organizing and conducting design and analytical sessions within the framework of the Agrofest-2019 festival was considered.
Games in School Libraries

The presentation will discuss how schools in the United States are using games to teach information literacy skills to students.
REKOMENDASI KEBIJAKAN REHABILITASI DAERAH IRIGASI SEBAGAI UPAYA MENINGKATKAN PRODUKTIVITAS HASIL PERTANIAN DI KECAMATAN KEDUNG GALAR, NGAWI JATIM

The Cepret Irrigation Area, located in Kedung Galar District, Ngawi Regency, East Java, irrigates agriculture, especially rice fields in Begal Village. The D.I Cepret irrigation channel, which should have irrigated rice fields with an optimal area of ​​611 hectares, is only able to irrigate paddy fields of 510 ha. This is due to damage to the irrigation canal, which requires rehabilitation. Rehabilitation of the D.I Cepret irrigation canal requires a benefit analysis and cost analysis to determine whether the costs incurred will be proportional to the benefits obtained. The method used for the analysis of benefits and costs is the calculation of the Benefit Cost Ratio (BCR). The costs analyzed are the investment costs for rehabilitation and operational costs as well as maintenance of the D.I Cepret irrigation canal, while for the analysis the calculated benefits are the increase in rice yields in Begal village. The final result of this benefit and cost analysis is the feasibility analysis of the irrigation canal rehabilitation project in Cepret. Based on the results of the calculation, it is known that the irrigation canal rehabilitation project in Cepret has an investment cost of 7,628,450,000.00 and maintenance and operational costs for 25 years of 18,639,112,038.46. The feasibility ratio using the Benefit Cost Ratio method is 2.91, which means that the rehabilitation of the D.I Cepret irrigation canal is declared feasible because the calculation of the Benefit Cost Ratio is worth more than one. DOI : https://doi.org/10.33005/adv.v9i2.2462
Türk ve Dünya Edebiyatından Eserlerin Doğal Dil İşlemeyle İncelenmesi / Analysis of Literary Works from Turkish and World Literature with Natural Language Processing

Publishers prepare and publish literary works from Turkish and world literature for the stages of primary, secondary and high schools. 5 literary works from Turkish and 5 from world literature having the same title prepared for the secondary school students out of 5 publishers were used in this study. Contents of these works works written in natural languages were analyzed with Turkish NLP techniques. It is aimed to reveal Turkish grammar rules and Turkish use in general and examine literary works specifically. Zemberek, NLP Library not only for Turkish but also for Turkic languages, were used in the examination of the words, determination of root/stem, spelling, affixation and identification of the types of the words. Other procedures except these were realized with the software specifically developed in C# language in Visual Studio environment for this study. Zemberek can analyze many of the words. In spite of the results which were obtained via analyses of literary works were found out as similar in terms of proportion, differences were found out in terms of unanalysable word number, average sentence number of literary works, average word number in literary works, average word number in a sentence and and the ratio of the use of dot and comma among publishers. When all the literary works are taken into consideration together, the following results were obtained: the average number of words in a sentence is 6.45, the average number of letters of words is 5.97, the average number of syllables of words is 2.55 and the average number of letters in syllables is 2.34. While the letters of A , E and I were the most used letters in literary works, J , F , P were the least used ones. Words mostly begin with the letters of B , K and D , rarely begin with the letters of J , I and L , and words mostly end with the letters of N , E and A , rarely end with the letters of C , B and J . Bigrams mostly end with the letters of A , E and I , rarely end with the letters of J , G and F . The most used syllable type is consonant-vowel (CV) and the least used syllable type is vowel-consonant-consonant (VCC) in the literary works. Most of the words were in accordance with the vowel and consonant harmonies. Moreover, approximately half of the words were in root form, in noun class and they were used without any affixation. The total number of use of inflectional suffixes were much more than derivational suffixes. The number of verb inflection suffix use is approximately half of the noun inflection suffix use. The number of verb derivational suffix is more than the noun derivational suffix. 12 punctuation marks out of 17 were included within the literary works. However, it was seen that the contents of literary works with the same name, which are prepared and published by different publishing houses, may differ partly or completely from each other.
Can You Tell? Ssnet - a Sagittal Stratum-Inspired Neural Network Framework for Sentiment Analysis

When people try to understand nuanced language they typically process multiple input sensor modalities to complete this cognitive task. It turns out the human brain has even a specialized neuron formation, called sagittal stratum, to help us understand sarcasm. We use this biological formation as the inspiration for designing a neural network architecture that combines predictions of different models on the same text to construct a robust, accurate and computationally efficient classifier for sentiment analysis. Experimental results on representative benchmark datasets and comparisons to other methods show the advantages of the new network architecture.
A Study on Blockchain Technology as a Dominant Feature to Mitigate Reputational Risk for Indian Academic Institutions and Universities

The paper-based certification is prone to manipulation and vulnerable to fraud. Instances of fraudulent degrees, manipulation of academic records, or compromised academic programs adversely impact and damage an academic institution's credibility. It also affects the Indian universities’ mission and prospects of the students graduating from such a university. What makes reputational risk a unique risk is that it may arise both from the university or institution's failure or the action outside the university. It is, therefore, essential to take an enterprise risk management approach to mitigate reputational risk. Robust credential verification and validation protocols are the most important protections against fake certifications. The legacy certificate verification solutions are highly centralized, i.e., utterly dependent on the issuing authority for certificates. Despite the University Grants Commission (UGC) taking strict measures against individuals, Indian universities, colleges, and associations, we do come across several acts of torts. Some of the technology-savvy institutions have moved to digital certificates and digital signatures. However, this has an inherent weakness, i.e., they still need to rely on a trusted third party. Blockchain technology has three foundational components, data structures based on cryptography that make it secure and tamperproof, consensus protocols that allow it to function truthfully and without any central authority or a third party smart contracts, which provide efficiency and business value transactions. These key features of blockchain, if implemented appropriately, effectively has the potential to mitigate the inherent reputational risk arising from fraudulent academic certificate matters. Niti Ayog is currently developing a blockchain-based proof of concepts to solve traditional educational qualifications related to identity misrepresentation and document forgery. The immutability attribute of the blockchain ensures that tampering and manipulation of the record are not attainable. This paper focuses on the reputational risk Indian universities and institution may face when its certifications are not easily verifiable. Therefore, it becomes easy targets for bad actors to exploit vulnerabilities by issuing counterfeit certificates. Secondary published data, including various scholarly journals, reports, industry publications, and website sources, are utilized to develop this case study. The paper also explores how blockchain technology with specific reference to the proof of concept SuperCert proposed by Niti Ayog for Indian academic institutions may provide effective preventive control to overcome such reputational risk using the ABCD analysis framework as a research case study.
몽골인 한국어 학습자의 오류 분석 연구 - 접속조사와 보조사를 중심으로-

In this study, the subject composition of 134 students in the first to fourth grades of the Korean language department at the International University of Ulaanbaatar in Mongolia was targeted for error analysis, and the errors of the conjunctive particle and auxiliary particle were identified.The results of a study, conjunctive particle was showed a relatively low error rate of 4.3%. Both of the errors were substitution errors, replacing ''(이)나'' with auxiliary particle ''(이)거나'' and allomorph of ''와/과.'' Auxiliary particle was showed an error rate of 21%. Among the 52 error frequencies, there were 21 substitution errors, 20 omission errors, and 11 addition errors. The addition error of the auxiliary particle was all caused by the ''unnecessary addition'' error.Along with the phenomenon of error, the cause was also analyzed to help us understand the background of the error. This will serve as a kind of guide for the future direction of education and emphasis in education, and help the learner understand the significance of learning, and the errors.
Methods of formation of spiritual and moral competencies in the education of future teachers

Measures aimed at forming a harmonious generation, educating young people spiritually and morally, turning them into an active participant in the ongoing reforms are being consistently implemented. Increasing the professionalism and competence was recognized as the main driving force of progress and activities leading to the goals of sustainable development. The modern education system involves the further improvement of the mechanisms for raising the competence offuture specialists on the basis of a creative approach and an innovative system for putting them into practice. From this point of view, the research competence of future specialists on the basis of a creative approach is of particular importance for creating innovation, creating intellectual resources for socio-economic development through the development of cognitive and divergent thinking based on modern pedagogical processes that create new knowledge, and expanding the training opportunities for competitive personnel. The article looks into the requirements and policies for the competent teaching staff.
Mammographic Image Segmentation using Automatic Evolutionary Algorithms

Breast cancer is noticed as the most common cancer and second main cause of cancerous deaths among women population in world wide. Many studies publicized that the early detection of breast cancer can cause longer survival rate. With the advent of new technologies in mammography, abnormality of masses can be effectively detected and diagnosed. Such Computer Aided Diagnosis and Detection(CADx, CADe) systems are automated and semi-automated systems help radiologists in early detection and diagnosis of breast cancer. The common phases of a CAD system are segmentation, feature extraction and classification. Efficient segmentation certainly can influence the subsequent phases of these systems. Clustering is a most common machine learning method in many segmentation applications including mammogram segmentation. Most of the segmentation methods are based on pixel intensity values and usually the segment with maximum intensity values is the region of interest. But in practice the complete segment may not contain abnormality. Abnormal mass is generally hard. This paper proposes a two phase evolutionary based segmentation combined with feature extraction for detection of regions of interests in mammograms using recent Automatic Clustering with simultaneous Feature Subset Selection for gray scale Image segmentation using Differential Evolution (ACFSDE).The proposed method has two phases; in the first phase suspected region is determined using automatic evolutionary intensity based segmentation. From the region hard mass area is determined using spatial information based segmentation. The second phase extracts textural features of each pixel by constructing GLCM which follows ACFSDE. Experiments are conducted on each image of MIAS database. The results demonstrated the accuracy and efficiency of the algorithm in identifying the masses of mammograms and the results are validated with ground truth.
An Efficient Coding Theorem via Probabilistic Representations and its Applications.

A probabilistic representation of a string x ∈ {0,1}ⁿ is given by the code of a randomized algorithm that outputs x with high probability [Igor C. Oliveira, 2019]. We employ probabilistic representations to establish the first unconditional Coding Theorem in time-bounded Kolmogorov complexity. More precisely, we show that if a distribution ensemble 𝒟_m can be uniformly sampled in time T(m) and generates a string x ∈ {0,1}^* with probability at least δ, then x admits a time-bounded probabilistic representation of complexity O(log(1/δ) + log (T) + log(m)). Under mild assumptions, a representation of this form can be computed from x and the code of the sampler in time polynomial in n = |x|. We derive consequences of this result relevant to the study of data compression, pseudodeterministic algorithms, time hierarchies for sampling distributions, and complexity lower bounds. In particular, we describe an instance-based search-to-decision reduction for Levin’s Kt complexity [Leonid A. Levin, 1984] and its probabilistic analogue rKt [Igor C. Oliveira, 2019]. As a consequence, if a string x admits a succinct time-bounded representation, then a near-optimal representation can be generated from x with high probability in polynomial time. This partially addresses in a time-bounded setting a question from [Leonid A. Levin, 1984] on the efficiency of computing an optimal encoding of a string.
APPLICATION OF REMOTE SENSING TECHNOLOGY AND GIS FOR MONITORING THE CHANGE OF LAND COVER DUE TO THE IMPACT OF BAUXITE EXTRACTION. CASE STUDY IN TAN RAI BAUXITE PROJECT, LAM DONG PROVINCE, CENTRAL HIGHLANDS REGION OF VIETNAM

In this study, we use Sentinel 2 satellite imagery and GIS technology to evaluate the dynamic of land cover around Tan Rai bauxite mining area, Lam Dong province (Central highland of Vietnam). 02 Sentinel 2 images taken on November 15, 2015 and December 3, 2020 with spatial resolution 10 m (band 2, 3, 4, 8) were used to classify the land cover using object-oriented classification method. The results of land cover classification are used for creating the land cover status maps from 2015, 2020, and then for mapping the land cover change in the period 2015 - 2020. The results obtained showed that there was a significant decrease in forest area, both dense forest and mixed forest, plantation forest. Meanwhile, the area of agricultural land and industrial crop land increased by about 10% in the period 2015 – 2020. The area of Tan Rai aluminum mining project in 2020 also increased to 376.47 hectares, nearly 2 times higher than 2015.
Comparison of Parameters of Sentimental Analysis Using Different Classifiers

Nowadays, we are seeing the surge of using social media as a platform for promoting and for any target. So, understanding the precise behavior of groups or individuals using his/her tweets or comments is the next step of sentiment analysis. We see innumerable knowledge shared on social media daily. We work on both sides on one side. We see various availability of data or opinions, and on the other hand, we challenge to group them in one centroid or domain in this work. We used the data of sentiment140 from Stanford University to perform various machine learning classifiers on feature extractors. Classifiers used in works are ridge classifiers, logistic regression, SVM, perceptron, passive aggressive classifiers, stochastic gradient descent, Naive Bayes, KNN, nearest centroid, and adaptive boost classifier. Our goal is a performance comparison of these classifiers on four performance factors namely recall, precision, accuracy, and F1 score. This work will help in consideration of selecting classifiers during sentimental analysis.
Applying the Fuzzy Decision-Making Method for Program Evaluation and Management Policy of Vietnamese Higher Education

Education policy is a dynamic process featuring social development trends. The world countries have focused their education program on empowering the learners for future life and work. This paper aims to assess the higher education curriculum based on a survey of 280 students, employers, alumni, and lecturers in both social sciences and natural sciences in Ho Chi Minh City, Vietnam. The fuzzy decision-making method, namely the Fuzzy Extent Analysis Method (F-EAM), was applied to measure the relative weight of each parameter. Seven factors under the curriculum development have been put in the ranking. Input with emphasis on foreign language was the highest priority in curriculum development, given the expected demand of the labor market. Objective and learning outcome and teaching activities ranked second and third, respectively. The traditional triangle of teaching content, methodology, and evaluation and assessment are still proven their roles, but certain modifications have been defined in the advanced curriculum. Teaching facilities had the least weight among the seven dimensions of curriculum development. The findings are helpful for education managers to efficiently allocate scarce resources to reform the curriculum to bridge the undergraduate quality gap between labor supply and demand, meeting the dynamic trends of social development.
TEKNOLOGI NON DESTRUKTIF DAN MACHINE LEARNING UNTUK PREDIKSI KUALITAS BUAH: TINJAUAN LITERATUR 2015-2020

Accuracy in the prediction of fruit quality is very important to provide the best products to consumers and increase economic value. To produce accurate prediction of good fruit quality, it is needed the right technological instruments and data processing techniques. In this literature review systematically summarizes and analyzes non-destructive technology and machine learning for the prediction of fruit quality over the past 5 years and its challenges and explores future opportunities and prospects for forming the latest references for researchers. Based on the results of the analysis that for accuracy and speed in the examination of fruit quality for internal and external attributes required different technological approaches, methods and algorithms according to their characteristics. Development of technology and algorithms continues to be achieved to achieve the goal that is the presence of fruit quality detection devices that are fast, reliable, portable, and cost-effective.
A hybrid Grey Wolf optimizer with multi-population differential evolution for global optimization problems

The optimization field is the process of solving an optimization problem using an optimization algorithm. Therefore, studying this research field requires to study both of optimization problems and algorithms. In this paper, a hybrid optimization algorithm based on differential evolution (DE) and grey wolf optimizer (GWO) is proposed. The proposed algorithm which is called “MDE-GWONM” is better than the original versions in terms of the balancing between exploration and exploitation. The results of implementing MDE-GWONM over nine benchmark test functions showed the performance is superior as compared to other stat of arts optimization algorithms
REPORTING INFORMATION SYSTEM OF PLANTATION PRODUCTS IN THE DEPARTMENT OF FOOD, HORTICULTURE AND PLANTATION

The Food Crops, Horticulture and Plantation Office is an agency that handles the plantation sector and becomes a facilitator in the availability of facilities and infrastructure. Good service and development to get maximum yields. The harvest data collection is still done manually by bookkeeping. The yield data that will be sent from the sub-district to the district can be said to be inefficient because in storing data manually there are many risks such as loss or damage. Storing the recap of harvest data in a book takes quite a long time. Seeing the problems that occur then with the report input facilities and print reports contained in the Plantation Product Reporting Information System at the Office of Food Crops, Horticulture and Plantations can facilitate the process of inputting the yields of sub-districts. The results of the UAT that have been done show that the system interface is good enough, in terms of ease of use the system gets a good response from users and in terms of system functions show the results that the system has been functioning according to user needs.  This system was built using waterfall development techniques and using the PHP programming language and using the MYSQL database. Keywords : Harvest Results, Regency, District, Plantation, Information System.