Reviewerly/exHarmony huggingface dataset:
THE PROCESS OF ASSESSING CORRUPTION RISK IN HIGHER EDUCATION

All government anti-corruption reforms in education are aimed at ensuring the rights and interests of citizens to receive a quality education. With the development of modern public administration and the rapid increase in the number of professions in the private sector, the fight against corruption in higher education is becoming increasingly important. The use of preventive methods in the fight against corruption is widespread in the world, and the use of this area in education provides high efficiency. Corruption risk assessment is one of the most common, integrated preventive methods in the fight against corruption. To this end, the article provides a scientific analysis of the concepts of “corruption risk assessment”, “procedure”, “methods”, and “stages” in higher education, and explains these concepts.
Enhancing Literacy Development in Nigeria through Reading and Writing Skills Development

Purpose: The Purpose of this paper is to draw the attention of the Government of Nigeria to the need to support the teaching of reading and writing skills in Nigerian schools for the much-needed national development.&#x0D; Method and data used: The research was carried out using the library research method which furnished the relevant information on the relevance of reading and writing skills in the acquisition of literacy, which is fundamental to Nigeria’s development.&#x0D; Finding: The goal of education in Nigeria is development. A kind of development that is human-centred and focused on the aptitude and achievements of an individual. Development is realised when there is a highly literate populace. However, this set objective is hampered by the growing rate of illiteracy. A UNESCO survey in 2015 reveals that 65 million Nigerians out of the 170 million Nigerians are illiterates. They can neither read nor write. The latest report from Varrella (2021) indicates that 62% of Nigerians are literate, even though not quite a good rate. Hence, a development that ought to be sustainable is threatened. The lukewarm attitude of the government in seeing that literacy gains prominence in the curriculum through reading and writing skills is dashed. With the poor literacy rate, it is appalling and a thing of grave concern for a nation that is focused on development through education to have more than half of its citizens as illiterates. Illiteracy is a clog in the wheel of sustainable educational development; it has placed the Nigerian state high on the global poverty index and exposed it to so many diseases and epidemics. Hence, illiteracy is linked to poverty.&#x0D; Unique Contribution to Theory, Practice and Policy: Furthermore, the paper found low literacy rate, inadequate funding of education and lack of professional literacy education teachers in the country and it concludes by strongly recommending the promotion of reading and writing skills through access to quality education, adequate funding of education and training of specialist teachers for the needed development of the nation, and sustain its future relevance in the comity of nations.
Personal Non-Property Rights of the Performer in Modern Conditions

Individuality and personal qualities manifistation is characteristic not only for authors when they create works, but also for performers. Performing a work, a performer leaves an imprint of his understanding of this work. Such an individual contribution gives grounds for the recognition of performers’ personal non-property rights to their performance. The personal non-property rights of the performer not only indicate the connection between the performer and the result of intellectual activity (performance) created by him, but they also allow the performer to terminate the actions of third parties affecting the personal interests of the performer. The paper provides a comparative analysis of the provisions of Russian and foreign legislative acts in the field of intellectual property concerning the personal non-property rights of performers. It is pointed out that the approaches applied to the protection of personal non-property rights of performers in the states of the Romano-German and Anglo-American legal systems have some differences. Thus, in the USA, provisions on unfair competition, privacy, etc. are applied to protect the non-property rights of performers. In Russia, when creating the provisions of legislation concerning the personal non-property rights of the performer, the provisions on similar rights of the author are taken as a basis, but in comparison with the authors, the rights of performers are more limited in scope. The author examines some problematic aspects indicating the expediency of studying the possibility of expanding the scope of the rights granted to the performer. In addition, it seems that the performer could have personal non-property rights that are not related to intellectual rights, for example, the right to an individual appearance and the right to vote.
Replication Package of "Evaluation Methods and Replicability of Software Architecture Research Objects"

In "Evaluation Methods and Replicability of Software Architecture Research" [1], we present a systematic literature review to assess the state-of-practice of evaluating software architecture research objects and providing replication artifacts in 153 full technical conference papers published at the International and European Conference on Software Architecture (ICSA respectively ECSA) from 2017 to 2021.
Effect of English Reading on the Cultivation of College Students’ Humanistic Spirit Based on Embedded Sensor System

With the development of information technology in recent years, people have integrated English reading with information technology, which is conducive to improving the ability of English reading and cultivating the humanistic spirit of college students. This paper aims to study how to play the role of English reading in the cultivation of college students’ humanistic spirit based on the embedded sensor system. This paper proposes an embedded speech recognition technology algorithm and a speech recognition technology algorithm based on dynamic time warping. Speech recognition technology is conducive to the improvement of English reading efficiency, as well as improving the reading interest of college students. The experimental results of this paper show that the speed of English development has become faster and faster in recent years, from 30% in 2011 to 55% in 2020. Although it fluctuates in the middle, the overall trend is upward. People pay more and more attention to English, and the proportion of English reading is gradually increasing, from about 20% in 2011 to about 41%. Therefore, it can be known that the importance of English reading is getting higher and higher, and it is necessary to cultivate the humanistic spirit of college students through English reading.
Quantitative evaluation of machine learning capability based on a differential game problem

With the development of artificial intelligence, various machine learning algorithms have emerged, but in the past, it was very inefficient to use machine learning methods to solve problems such as optimal control and problems of game theory, so a method that can quantitatively evaluate the machine learning capability is proposed, which can significantly improve the efficiency of existing algorithms. In this paper, a differential game problem based on the sheep-dog two-dimensional motion model is established and five related questions are answered according to the constraints in the problem. Meanwhile, the algorithm is analyzed quantitatively and the corresponding results are obtained. The paper also verifies that several models, equations of motion and machine learning algorithms established in this paper are reliable through sensitivity analysis.
Promoting Midwifery Students’ Speaking Ability Using Communicative Language Teaching

Speaking is the way to convey the information that must be acquired by students. Consequently, this study aimed to see whether Communicative Language Teaching could promote midwifery students’ speaking ability or not. In conducting this research, a quasi-experimental method was employed using a nonequivalent groups design. The sample taken was the second-semester student midwifery from STIK Bina Husada consisting of 38 students. To gather data, the oral test was employed. The speaking test was considered valid in terms of content validity and reliability. The reliability of the test was measured using inter-rater reliability. The results revealed that the t-obtained (5.42) was higher than the t-table (2.02) at the significant level of p&lt;0.05. It can be concluded that Communicative Language Teaching could promote students speaking ability. Communicative Language Teaching could motivate students to be brave and self-confident in speaking performance and more active in using English as their spoken language in-class activities.
Analisis Cluster Untuk Pengelompokkan Prestasi Mahasiswa Angkatan 2013 Fakultas MIPA Universitas Islam Madura

Student achievement is a person's mastery of certain knowledge or skills in a course, which is obtained from test scores or numbers given by the lecturer. Many factors affect student achievement, including parents' income, pocket money, distance to campus, length of time studying, student side jobs, and the existence of learning aids. Therefore, a research will be conducted using cluster analysis for grouping student achievement in the hope of mapping students so that it is easier for lecturers to teach students. In this case, four cluster analysis methods are used, namely single linkage, complete linkage, average linkage and k-means. Where the best grouping is obtained with the icdrate, namely average linkage. The results of the average linkage method obtained that the two groups were the lowest of the other five groups who had to get more guidance from other groups.
Peningkatan Hasil Belajar IPS Melalui Problem Based Learning di SMP Negeri 5 Wates

This study aims to improve social studies learning outcomes in class VIII students of SMP Negeri 5 Wates. Teachers need to take classroom action by improving the monotonous learning process, namely lecture learning using the Problem Based Learning model. The research method used is Classroom Action Research with 2 cycles, which includes planning, action, observation and reflection steps. Data collection techniques used are observation and tests. The collected data were analyzed by quantitative descriptive technique with percentage technique. The results of this study indicate that: 1) Problem Based Learning model is more interesting for students to learn and can improve students' social studies learning outcomes. 2) Learning outcomes in the initial conditions obtained an average score of 55.6 with students who completed a total of 31.25%, after using the Problem Based Learning model in the first cycle obtained an average score of 68.0 with 56.25% complete participants. Then after repairs were made in the second cycle, the average was 76.9 with 78.13% of students completed.
Automatic Hand Gesture Recognition System using Raspberry Pi

This undertaking’s principle objective is to shed some light on deaf and dumb people facing communication difficulties. Various methodologies have been introduced in hand gesture recognition, yet at the same time, research is limited. This paper mainly focuses on the automatic hand gesture recognition system in real-time using a powerful compact, yet resource constraints device called Raspberry pi. We have used the Pi 3B+ model. We have trained the Convolutional Neural Network (CNN) to recognize the hand gesture. In this, we created a python script to take our trained model and then recognize hand gestures in real-time. We used Intel Movidius Neural Compute Stick to achieve an accuracy of 99% in executing it, along with the low computational cost.
Low Resource Style Transfer via Domain Adaptive Meta Learning

Text style transfer (TST) without parallel data has achieved some practical success.However, most of the existing unsupervised text style transfer methods suffer from (i) requiring massive amounts of non-parallel data to guide transferring different text styles.(ii) colossal performance degradation when fine-tuning the model in new domains.In this work, we propose DAML-ATM (Domain Adaptive Meta-Learning with Adversarial Transfer Model), which consists of two parts: DAML and ATM.DAML is a domain adaptive meta-learning approach to learn general knowledge in multiple heterogeneous source domains, capable of adapting to new unseen domains with a small amount of data.Moreover, we propose a new unsupervised TST approach Adversarial Transfer Model (ATM), composed of a sequence-to-sequence pre-trained language model and uses adversarial style training for better content preservation and style transfer.Results on multi-domain datasets demonstrate that our approach generalizes well on unseen low-resource domains, achieving state-of-theart results against ten strong baselines.
Prediksi Harga Saham Subsektor Farmasi Menggunakan Geometric Brownian Motion

Investing in stocks is a popular type of investment today. During the current COVID-19 pandemic, the shares of companies in the pharmaceutical sub-sector are becoming more attractive. Stock price movements determine whether investors will increase their investment in a company or withdraw their money. To minimize the risk of investor loss, forecasting is carried out on the daily closing of stock prices. Forecasting is the best method to predict future stock prices Geometric Brownian motion is a method used to predict time series data, where random variables follow Brownian motion. In this study, simulation and analysis of stock returns and fluctuations (volatility) of 5 companies from the basic industry and chemical sector (Basic Industry &amp; Chemicals), pharmaceutical sub-sector on the IDX will be carried out. The five companies are PT Darya-Varia Laboratoria Tbk (DVLA), PT Indofarma (Persero) Tbk (INAF), PT Kimia Farma (Persero) Tbk (KAEF), PT Kalbe Farma Tbk (KLBF), and PT Industri Jamu and Pharmaceutical Sido. Muncul Tbk (SIDO). After the Kolmogorov-Smirnov normalization test, the stocks that meet the normal distribution are KLBF and SIDO. Then the predicted MAPE value of the two stocks is calculated. The MAPE values for KLBF at 100 iterations, 1000 iterations and 10000 iterations were 2.1073%, 1.4382% and 1.2847%.. MAPE values for SIDO at 100 iterations, 1000 iterations and 10000 iterations are 2.0136%, 2.2568%, and 2.0677%.
Convolutional denoising of underwater laser line scan images via transfer learning

In this paper, we consider the problem of Poisson noise suppression in underwater laser line scan (LLS) imagery for image quality enhancement. We investigate two different denoising neural network architectures, one based on a convolutional autoencoder (CAE) and a commonly used convolutional neural network (CNN) based denoiser. Due to the relative abundance of camera images over underwater LLS imagery, we employ transfer learning with camera images as training data for the CAE and CNN architectures. Poisson noise is introduced in these training images at varying levels to mimic a noise-dominated LLS system. Images from an underwater scene under different turbidity conditions are used for testing. Using a composite loss function consisting of l1 and l2 norms, we demonstrate the noise suppression capabilities of both architectures in underwater LLS images via transfer learning. The results show that the CAE outperforms the CNN denoiser qualitatively and quantitatively in terms of the contrast ratio and contrast signal-to-noise ratio.
TRANSFER LEARNING IN THE CLASSIFICATION OF SATELLITE IMAGES SHOWING AMAZON RAINFOREST

Abstract. In recent years, we have been dealing with the dynamic technological progress of the space sector, which allows for the observation of the Earth with better temporal, spatial and spectral resolution. The increasing availability of satellite data has contributed to the development of data processing algorithms. Thanks to the use of digital image processing methods and deep neural networks, it is possible to perform automatic image classification, segmentation or detection and recognition of objects on the images. This article presents the methodology that allows to accelerate the classification process of satellite images representing the Amazon rainforest based on the Transfer Learning method. Additionally, the influence of the choice of optimization, i.e. the network weight estimation strategy, on the classification of objects was checked. In order to verify the method, an additional raster image classifier was created on the basis of Lidar data. Research shows that the transfer learning method allows the preparation of an image classifier based on a small database (less than 100 images representing one class). The network training process can be shortened to a few minutes.
THE EFFECT OF A VIDEO-AID CONTEXTUAL APPROACH TO THE EFFORTS OF IMPROVING THE ABILITY OF WRITING STORY TEXT IN CLASS IX JUNIOR HIGH SCHOOLS

The students' difficulties in understanding the material and the lack of interest in learning in learning to write short story texts were the background for this research to be conducted. A contextual approach assisted by instructional video media is used to overcome this problem. The formulation of the problem is whether there is an effect of using contextual approaches assisted by instructional videos on students' abilities in learning to write short story texts. The method used in this research is quantitative descriptive method using written test instruments as a tool to determine students' writing skills. Following are the results of the average score that students have at the time of the pretest getting 60.32 and the posttest getting 75.54, it can be seen that there is an increase in the value of 15.22 points. In line with the results of the paired sample test, which obtained a significance value (2-tailed) of 0.000 &lt;0.005, it means that Ha is accepted. So it can be concluded that the use of a contextual approach assisted by instructional videos in learning to write short story texts can improve students' writing skills.
Rancang Bangun Sistem Aplikasi Rehabilitasi (SIREHAB) dalam Pengelolaan dan Pengendalian Pecandu Narkotika dengan Menerapkan Metode Agile Software Development di Wilayah POLDA Jambi

Drug abuse is currently a very serious threat to the current generation. The current danger of drugs is so terrible that the government has to deal with drug abuse and drug addicts by means of rehabilitation. The National Police of the Republic of Indonesia, in particular the Directorate of Drugs and the Jambi Regional Police, based on the provisions of the applicable laws and regulations, regarding rehabilitation and narcotics addicts have an obligation to carry out a rehabilitation program. However, nationally, especially in Jambi Province, there is currently no reporting system on the management and control of narcotics addicts data online while based on 2021 data, the data on narcotics addicts is quite high, so it requires a system for monitoring the rehabilitation data for narcotics addicts to make it easier to monitor. its existence. In order to overcome the existing problems, the author wants to help and make it easier by designing and building an information system for the rehabilitation of narcotics addicts in the Jambi Regional Police area using the agile software development method. The purpose of building a system using this method is to assist and facilitate the management and control of narcotics addicts in the Jambi Regional Police by involving maximum involvement of stakeholders and related parties, especially the Narcotics Directorate and Jambi Regional Police so that the use of applications is more adaptive and can be developed more widely. more in responding to the challenges and changes that exist. The result of this research is that the system development is carried out using the agile software development method using six stages, namely meetings (meeting), planning (plan), design (develop), testing (test), and evaluation (evaluation). Based on the results of system testing carried out using black box testing, the system was as expected
Collaborative Cluster Configuration for Distributed Data-Parallel Processing: A Research Overview

Abstract Many organizations routinely analyze large datasets using systems for distributed data-parallel processing and clusters of commodity resources. Yet, users need to configure adequate resources for their data processing jobs. This requires significant insights into expected job runtimes and scaling behavior, resource characteristics, input data distributions, and other factors. Unable to estimate performance accurately, users frequently overprovision resources for their jobs, leading to low resource utilization and high costs. In this paper, we present major building blocks towards a collaborative approach for optimization of data processing cluster configurations based on runtime data and performance models. We believe that runtime data can be shared and used for performance models across different execution contexts, significantly reducing the reliance on the recurrence of individual processing jobs or, else, dedicated job profiling. For this, we describe how the similarity of processing jobs and cluster infrastructures can be employed to combine suitable data points from local and global job executions into accurate performance models. Furthermore, we outline approaches to performance prediction via more context-aware and reusable models. Finally, we lay out how metrics from previous executions can be combined with runtime monitoring to effectively re-configure models and clusters dynamically.
Learning Process of Online Class by Using Language Politeness Principles

This article results from research on language politeness in the learning process in the "Language Curriculum Evaluation and Design" class. Leech's politeness principle theory consists of six maxims: tact maxim, generosity maxim, appreciation maxim, modesty maxim, agreement maxim, and sympathy maxim. This study aimed to find out the language politeness used in that class. Then, this study focused on the Lecturer's utterances to the students. The type of this study was descriptive qualitative. The instrument of this study was the researchers themselves and the audio recorder. The technique of collecting the data was tapping techniques to tap the conversation of the Lecturer with the students, field notes and observation. This research showed that Leech's politeness principles were used in that class. The maxim of politeness included tact maxim 22,7%, generosity maxim 13,6%, appreciation maxim 18,2%, modesty maxim 9,1%, agreement maxim 18,2%, and sympathy maxim 18,2%. Most of the maxims used in that class are tact maxims. After analyzing these six maxims, it is essential to have them when we are a lecturer teaching in the class. A teacher with the six maxims can control the class to run well.