Reviewerly/exHarmony huggingface dataset:
University Dropout: An experience from the School of Higher Studies in Jojutla

This article identifies the different factors that lead students to drop out of their university studies within the period that comprises this stage in the bachelors degrees offered by the School of Higher Studies of Jojutla (EESJ by its acronym in Spanish), which depends on the Autonomous University of the State of Morelos (UAEM by its acronym in Spanish)) from the implementation of the current study plans.The relevance of the research carried out lies not only in the continuous improvement of the institution, but also in providing tools to the competent bodies through research instruments and concrete data to prepare a proposal that contributes to reducing dropout within the campus.The Professional Institute of the South Region, today the School of Higher Studies of Jojutla, begins as a project that gives rise to an Institute, which was approved by the Honourable University Council, beginning on July 16, 1993.Throughout its history, it has been gaining prestige as it is a public institution in the region that offers a quality education with easy access to low-income people in public accounting, business manager and law bachelors degrees, currently with an enrollment of 730 students, which has also increased according to population needs.It was certified in 2017 by the Inter-Institutional Committees for the Evaluation of Higher Education (CIEES by its acronym in Spanish), an organization dedicated to ensuring the quality of higher education, culminating this process with a report that revealed areas of opportunity to improve the quality of education.Among its strategic lines of action is to promote studies and give permanent follow-up to the problem of retention of the student population and design programs to reduce dropout.The results presented here correspond to a sample of 177 students from the total number of dropouts from the different courses.Such results will allow us to know the factors that influence the decision to drop out of their university studies and define the relationship that the study plan has with this decision.
KEANEKARAGAMAN TUMBUHAN PAKU (PTERIDOPHYTA) DI DAERAH ALIRAN SUNGAI PEPUWATU DESA PRAI PAHA KABUPATEN SUMBA TIMUR SEBAGAI SUMBER BELAJAR BIOLOGI

This study aims to describe the diversity of ferns found in the Pepuwatu River Basin, Prai Paha Village, East Sumba Regency, and to describe the ferns in the Pepuwatu River Basin, Prai Paha Village, East Sumba Regency as a learning resource. Biology in booklet form. This type of research is ecological research with a quantitative descriptive approach. The method used is the eruise method. The results of the study found 450 individuals from 15. The index of fern diversity in the Pepuwatu River watershed was 1, 948 in the medium category. The product produced in the study is a learning resource in the form of a booklet. Based on the results of the booklet validation test from validator I, which is 100%, validator II is 98.33% and validator III is 96.6%. This means that this booklet is feasible to use in supporting the learning process.Kata Kunci : sumber belajar biologi, keanekaragaman, tumbuhan paku.
Masked Face Recognition and Temperature Monitoring Systems for Airplane Passenger Using Sensor Fusion

Transportation is currently an unavoidable necessity. However, the COVID-19 pandemic has impacted all lines of industry, including the Indonesian aviation transportation industry. Technology is one of the solutions to deal with these problems. The monitoring system of masked face recognition and body temperature detection for the check-in process of passengers at the airport is aimed to be developed in this research. The contribution of this research is that the system can distinguish the type of face mask used. Therefore, this monitoring system classified only medical masks and N95/KN95 respirator masks as ‘Good Masked’. IP camera and thermal camera are used to identify a masked face and body temperature, respectively. The sensor fusion method was used for decision-making on passengers whether they can be departed or not. The decision was taken based on the measured body temperature, the use of standardized face masks, and the face recognition of the airport passengers. Convolutional neural network (CNN) method was used for face and face mask recognition. The CNN model training was conducted four times according to the four proposed scenarios. The CNN model that has been trained can distinguish a masked face and a face without a mask. The best results were obtained in the fourth scenario with the comparison of the training dataset to the testing dataset was 9:1 and the epoch was 500 times. The basic deep learning model used for face detection was the single shot multibox detector (SSD) using the ResNet-10 architecture. Meanwhile, the CNN method with the MobileNetV2 architecture was used to detect the use of masks. The accuracy of the CNN model for face recognition and mask recognition was 100%. All check-in monitoring and verification process data were displayed on the web application which was built on the localhost.
Speaking Anxiety in Online English Class: Causes and Effects

This research analyzed speaking anxiety that occurred in English Classes at the Faculty of Ushuluddin and Humanities UIN Walisongo Semarang. The aim of this research is to analyze students’ speaking anxiety and its cause and effects. Research participants were students of the Faculty of Ushuluddin and Humanities UIN Walisongo who took the English Class in Academic Year 2021/2022. The total sample was 86 students out of 417 students. This study used questionnaires and interviews as a data collection method. The finding showed that most students have a high level of speaking anxiety. The interview also showed that students’ anxiety was caused by lack of vocabulary, problems with confidence, making mistakes fears and shyness.
Psychological and Pedagogical Features of the Development of the Imagination of Primary School Students in Visual Activity

The relevance of the study is due to the problem of developing creative abilities and the formation of imagination in the process of visual activity of primary school students. The chapter deals with the main psychological and pedagogical processes of the formation of the imagination of children aged 7–9 years at the lessons of fine arts in the process of artistic and creative activity. The development of creative abilities is one of the key tasks of modern education. Imagination helps the child to better understand the world around him, easier and more successfully solve the educational problems that arise in front of him.
Hand Gesture Recognition

Abstract: Hand gesture recognition system has evolved within the recent few years due to evolving of technology and mostly due to device dependent life. People are now turning towards technology for a far better life with computer and portable devices being an enormous part of it. Not only people but companies too are shifting towards technology for improved performance of their products. Keywords: Hand gesture, computer vision, deep learning, feature extraction classification, Neural network.
Electronic Banking and Economic Productivity in Nigeria

This research paper electronic banking and economic productivity in Nigeria.Secondary data were sources from CBN statistical bulletin Real Gross Domestic Product (RGDP) and electronic banking (ATM, POSand Mobile banking) for the period of 2009 to 2019.The collected data was analysed using ordinary least square (OLS) regression technique.Findings of the research revealed that ATM and MPS has positive and significant relationship with economic productivity while POS shows negative and inverse relationship with economic productivity.The paper concludes from its findings that electronic bankinghas mixed effect on economic productivity of Nigeria.Thus, while ATMand mobile banking leads to improvements in economic productivity, same cannot be said for point of sales machines which has a negative effect on economic productivity.The study recommends that regulatory authorities should investigate further on the usage of point of sales since it asserts negative effect on economic productivity in Nigeria.The study also proffers that there is need for improvement on the performance of automated teller machine and mobile payment system since they assert positive and significant impact on economic productivity.
A Survey on Real Time Sentiment Analysis Based on Social Media Mining

Abstract: Social media is a platform where people from any corner of the world share their opinions with each other. Thus current era is called as social media era. Social networking sitessuch as Facebook and Twitter plays an important role in information retrieval and web data analysis. In a survey it is found that Twitter produces more than 500 million of tweets each day which is about 8 TB of data which can be mined and sentiments analysis can be carried out. The purpose of mining and exacting opinions is todiscover and categorize the positive and negative sentiments of society. So as there is a huge repository of data, clustering is efficient and quickway to study people’s expression and get aconclusion. This paper surveys the different mining techniques to carry out opinions and sentiments analysis and represent it to the bestway based on subjectivity and polarity. Keyword: Social Media, Opinion Mining, Sentiments Analysis, Clustering, Expressions, Social Networking.
Smart Voting System Using Deep Learning and Computer Vision

Abstract: Since, India being the largest democracy in the world. Still uses voting machines to hold elections, which comes with high costs and manual labour. But voting plays a crucial role in the election of high-ranking government officials and reflects our view of how a governing body should be formed. Investigations are conducted from time to time to troubleshoot the central voting system, increasing anonymity, credibility and security while preventing all types of fraud. In this paper, there is an implementation of a method that uses deep learning techniques which develops a smart voting system. Due to its advanced features, most researchers follow and use the Boosted Cascade framework. The enhanced Cascade Framework features help you calculate and build a classifier that works more accurately. However, this accuracy rate requires a large number of Cascade Stages to help reduce similar performance with the detection and recognition accuracy. This provides protection in the sense that the most secure voter password is verified before a vote is received on the main database of the Indian Electoral Commission and voters can verify that his or her vote has reached to correct participant of election. The votes counting is done automatically, thus saving a lot of time and the results can be announced in a very short time by the Indian Electoral Commission. The user verification process is enhanced by adding a face recognition to the app that will determine whether the voter is a certified user or not. Keywords: Online voting system, smart voting, face recognition, face detection, security, user authentication, deep learning, haar cascade classifier, computer vision.
Characterization of Side Channels on FPGA-based Off-The-Shelf Boards against Automated Attacks

FPGAs offer fast and reliable near-data processing and are therefore suitable candidates for implementing IoT and edge computing systems. As they are usually deployed in exposed locations, they are vulnerable to physical attacks, especially Side-Channel Analysis (SCA).In this paper, we characterize side-channels and how they can be exploited for SCA on FPGA-based off-the-shelf boards, i.e. without having to make any modifications to the board, hardware, or software. The basic requirement for any kind of SCA is that the individual Cryptographic Operations (COs) in the side-channel traces can be detected.To this end, we apply a SCA for semi-automatic CO detection that can be generically applied off-the-shelf to a wide variety of boards. Additionally, we introduce a new metric called Signal of COs to Noise Ratio (SCONR), that allows to quantify the pronouncedness of COs versus noise in a side channel. We then evaluate side channels measured on three different boards containing Xilinx 7 series FPGAs. We further investigate the influence of other sources of noise and how much they affect the attackability of a system.Our results show that FPGAs have a high vulnerability to SCA in general and that even noise from an operating system will not hinder the recording and finding of COs in an automated fashion as long as there are no countermeasures in place. Finally, SCONR converges after fewer recorded traces and gives a clearer indication whether a side channel is susceptible to this type of automated attack than leakage assessment techniques such as TVLA.
UnFlowGAN: Unsupervised Learning of Optical Flow with Adversarial Learning

Recently, unsupervised learning-based approaches for optical flow estimation have been actively researched. In unsupervised settings, the difference between the input image and the reconstructed image created from the estimated optical flow is minimized to learn the optical flow. Conventional learning methods mainly treated the difference as the pixel-by-pixel brightness error, which might lead to decreasing accuracy of the optical flow because the learning-strategy cannot take the textures into account sufficiently. To deal with the problem, in addition to the brightness error, we propose the introduction of adversarial learning into the evaluation of the input image and the reconstructed image. Our main contribution is that we develop a learning-strategy to capture the textures and the proposed method outperforms the conventional methods on the KITTI benchmarks.
To the Question of "Germanophobia" in the Autobiographical Story of the Russian Officer V.V. Korsak during the First World War

Barges of the domestic merchant and military fleets have not yet been the object of scientific research.Many authors dealing with the history of shipbuilding mention the construction of non-self-propelled ships, but these are only eclectic references.Partially, this problem is overcome by statistical collections that published the composition of the merchant and military fleets on a certain date.However, a holistic picture of the evolution of the domestic non-self-propelled fleet is created either for the pre-revolutionary or for the Soviet period.The events of the revolution and the civil war pass by a kind of watershed, which makes it difficult to reliably connect the biographies of the vessels.In [1916][1917] The Votkinsk plant received an order from the Maritime Ministry for the construction of 20 barges of a 250-ton raid and 200-ton river type.The entire order was fulfilled by the plant, but with some delay, given the "force majeure" of 1917-1918.These barges became the object of study of this work.Of the ten barges of the 250-ton type, seven were handed over to the customer and became part of the watercraft of the Arkhangelsk military port.Three more, apparently, at the time of the start of active hostilities on the Northern Dvina were under construction.Since this type was not well suited for fighting on the rivers, all three barges were transferred to the Upper Volga.Of the ten barges of the 200-ton type, within the existing source base, it is possible to trace only the biographies of five that entered the Kama River Shipping Company, and later the Vyatka.Most likely, at the time of the beginning of the Votkinsk uprising, these five barges were located in the city, used first as a prison, and then floated to the Kama to build a pontoon bridge.The fate of five more barges is unknown.If they did not die during the civil war, it is possible that they were assembled without the participation of the Votkinsk plant and the plant no longer appeared in their further registration data.
Exploring the Impacts of Multiple Kernel Sizes of Gaussian Filters Combined to Approximate Computing in Canny Edge Detection

Image processing applications are currently available on mobile devices, stressing the energy efficiency demands during the hardware design. In these applications, image edge detectors use filters as a preprocessing step to reduce undesirable artifacts and smooth the image. This work explores the combination of Multiplierless Multiple Constant Multiplication and Approximate Computing techniques on the Gaussian filter, investigating three different kernel size impacts on image processing. The impact of approximation is evaluated at different levels using the copy strategy technique on the LSBs of adders. The results show power and area reductions for the kernel sizes under evaluation. For instance, the approximate kernel <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$7\times 7$</tex> kernel achieved reductions of up to 40% and 48% for the area and power consumption, respectively, compared to the exact version. It shows ample space for design exploration targeting different trade-offs of quality and power results.
A Study on the Improvement of the Curriculum of Chinese University Korean Language Department through Needs Analysis: Focusing on the Case of the Korean Language Department of Y University

With the increasing exchanges in the fields of politics, economy and culture between Korea and China, the Korean language education in China has increased rapidly. At the same time, Korean language education needs more advanced education concepts and new curriculum to provide students with a high quality Korean language learning environment. Checking and supplementing the contents and effectiveness of the curriculum is a necessary condition to maximize education effects and foster high-level Korean talents who can communicate in a high-level manner. But there are not many previous studies that suggest improvement about Korean language curriculum of Chinese universities through needs analysis. The purpose of this study is to find an efficient improvement plan for the curriculum of the Korean language department of Chinese universities through needs analysis with the curriculum of Korean language department of Y University, which is recognized for its relatively high proficiency in China. To this end, detailed questionnaire surveys and interviews were conducted on two groups of students and teachers with six items such as ‘curriculum goal’, ‘course setting’, ‘classroom lecture’, ‘self-learning’, ‘capability evaluation’, and ‘textbook satisfaction’. Through the analysis of the results, we identified students and teachers’ perceptions and needs of the curriculum and derived problems of the curriculum. We also presented reasonable improvement directions to problems of the curriculum identified through this needs analysis.&#x0D;
Analysing the Cloud Data Storage Technology and Its Architecture Applications

The idea of using the internet to store data in the cloud is becoming more popular these days. Cloud computing data storage is the most crucial and significant research topic. The article begins with an introduction to cloud computing, storage in the cloud, and architecture for storage in the cloud. GFS (Google towards genuine corporate examples) and HDFS (Hadoop Distributed File System) are the cloud data storage technologies that we examine next (Hadoop Distributed File System) With that, we come to the end of our series. We show how to enhance the conventional method of storing files using the eyeOS Web operating system. Distributed storage and fault-tolerant control are provided by HDFS, a component of Hadoop. Keywords: “Cloud Computing; Cloud Storage; Web Operating System; Distributed File System”
Investigating the Current Status of School Drop Prevention Policies and Projects: Focusing on Policy Improvement Measures

The purpose of this study is to draw implications for policy improvement by identifying the current status of school drop prevention policies and projects being operated at school sites. To achieve this objective, a survey was conducted with school teachers in charge of the nationwide school drop prevention projects. A total of 1,575 people responded to the survey. The results of analyzing the school members’ perceptions of the school drop prevention projects, the current status of business operations, difficulties, and areas for improvement were analyzed as follows. First, the designation of the school drop prevention projects and the operation of the deliberation systems are concentrated at the high school level. Considering the accumulated situations of the academic discontinuation, it is necessary to activate projects in both elementary school and high school level. Second, the operation of alternative classrooms in schools was in the order of middle school (39.8%), elementary school (6.4%), and high school (27.3%). In particular, it is necessary to understand the difficulties in operating alternative classrooms in elementary schools. In addition, it is necessary to prepare a way to overcome stigmas and prejudices, and a plan to link the curriculum of alternative classrooms in high schools. Third, the significance and necessity of the study regarding the school drop prevention projects were found in the order of providing emotional stability (4.08 points), providing time and space for rest (4.07 points), helping with school adjustment (3.94 points), and providing customized education (3.92 points). Therefore, it is necessary to provide programs and opportunities for students to solve problems according to their situation. Fourth, the difficulties of the school drop prevention project were derived from the overload of the person in charge, the lack of connection to external organizations, and formal and superficial work procedures. Therefore, it is necessary to improve policies such as assigning one or more professional counselors to schools, providing incentives for those in charge, support from the office of education for linking external instructors with local community organizations, and discovering and expanding entrusted educational institutions for alternative education with expertise.
Modern Sound Recording Technologies

The purpose of the article is to investigate modern sound recording technologies; analyze the structural components that affect the sound formation of audio-visual content. The research methodology consists in the application of the following methods: theoretical method (consideration and structure of sound recording equipment as a process of transforming sound from analogue to digital and vice versa); analysis and synthesis (to analyze the work of sound recording technologies in the modern media space); systematization (a generalization of the material in the conclusions). The scientific novelty lies in the differential approach associated with the stage of sound recording perception, from analogue-digital signal to digital-analogue one, as a means of influencing the increase of sound level at the final stage. Conclusions. Under the influence of the widespread use of audio-visual content, the study analyzed the components of the sound recording equipment aspects and sound reproduction in general. Structural components that are a component of factors influencing the formation of sound have been considered in detail.