Reviewerly/exHarmony huggingface dataset:
Rhythm and Vocabulary of Greek Hexameter: From Formula to Topolexis

The article discusses the results of our application of a computer program created for the automatic analysis of lexical distribution based on rhythmic position in Greek hexameter. For this purpose, we introduce the concept of the topolexis (in Greek τοπολέξις: from τόπος “place” and λέξις “expression, word”), which describes each word based on its position in the given line and is expressed as the word in combination with two sets of numerals. The topolexis “52Ἀχιλῆος62”, for example, indicates that the word Ἀχιλῆος begins at the second syllable of the fifth foot (52) and ends at the second syllable of the sixth foot (62). We investigate the behavior of topolexes in a corpus that includes Homer’s The Iliad and The Odyssey and Apollonius Rhodius’ The Argonautica. We find that the distribution of topolexes of different frequencies varies among these texts. While The Argonautica contains a greater number of unique topolexes, higher-frequency topolexes are more common in Homer’s poems. The “formulaicity ratio”, which we define as the ratio of distinct topolexes in a text to its overall topolexis count, is higher for Homer. In addition, we obtain and analyze data about Hesiod’s The Theogony. Although The Theogony is only 1,023 lines long, it exhibits the same tendencies as Homeric hexameter. We are, thus, able to clearly and accurately compare the behavior of topolexes in epic hexameter in the formulaic style and in its literary imitation by Apollonius. Lastly, we run a test to compare the performances of the topolexes and the most frequent words (MFW) as stylometric indicators for determining text authorship. We find that while topolexes enable us to correctly cluster fragments by their author, they do not outperform the MFW in this respect.
PROSPECTS, PROBLEMS AND POSSIBLE OPPORTUNITIES OF DIGITAL CURRENCY IN BANGLADESH

This study attempts to present the prospects and problems of the digital currency in Bangladesh as well around the world. To demonstrate the prospect, price and trading volume of selected ten digital currencies being presented for observing the emerging the demand. From our country's perspective, the opinions of the respondents collected through questionnaires shed light on the prospect of digital currency in Bangladesh. Additionally, the study presents a systematic literature review (SLR) of research on digital currency. The review incorporated 11 articles presenting several issues related to digital currency. This study uses data from 2013 to 2020 for respective currencies related to price and trading volume. As well respondent’s opinions collected through “questionnaires” are presented as per percentage. This study also makes theoretical contributions to the extant literature. The findings demonstrate that digital currency is now successfully traded in the most countries around the world except a few. Descriptive statistics of price and trading volume indicate that most of the variables are highly skewed with large outliers and kurtosis column shows that all the variables are near to normal distribution and investment regarding these values indicates a safe trading. The consents of 175 respondents present a positive attitude of the general public towards digital currency. The SLR methods suggest that a secure system and advanced technology should be attached to the block chain system to ensure better performance. The SLR findings also point out that digital currency is obviously a better alternative to cash, although it has some risks.
Analýza stokovej siete v meste Trnava

A typical object on uniform sewer networks are relief chambers, which serve to regulate the flow of rainwater.Their task is to reduce the amount of rainwater supplied to the wastewater treatment plant and thus protect it from overload.These waters are a mixture of sewage and surface runoff water and therefore contain various contaminants.In the city of Trnava, reduced water quality was recorded in the Trnávka recipient.It is therefore necessary to determine the current state of these chambers and to determine whether they comply with current environmental regulations.
SMART HEALTH MONITORING SYSTEM UTILIZING INTERNET OF THINGS (IoT) AND ARDUINO

The use of healthcare monitoring systems in hospitals and other health facilities has grown exponentially, and portable healthcare monitoring systems based on new technologies have emerged as a severe concern in several countries throughout the globe. The emergence of the Internet of Things (IoT) technology has contributed to the progress of healthcare from face-to-face counseling to telemedicine. The project aims to design a reliable health monitoring system utilizing the IoT, Arduino, and Android applications. It can be used to measure body temperature, heart rate, and level of oxygen in the blood in both hospitals and homes. The system is also capable to verify that the transmission of the sensor’s data to the host computer is done in real-time. The results show that the system reading is approximately 100% accurate as of the purchased measuring instruments or actual devices. Therefore, doctors and family members can now monitor and track the patient’s health anywhere through this smart health monitoring system.
Development and Implementation Path of Kindergarten Stem Educational Activities Based on Data Mining

Early childhood education in China has given stem education constant attention and study. On the one hand, it has introduced many foreign research findings on stem education, such as curriculum practice, evaluation systems, teacher training, and so on; on the other hand, this paper investigates the localization implementation path of stem education based on the realities of kindergartens. This paper investigates the development and implementation path of kindergarten stem education activities using data mining, analyzes how the kindergarten stem education monitoring index system is developed and further improved using data mining algorithm, and determines the function path and mode of data mining algorithm in kindergarten stem education. It is expected to be used as a reference in the development and implementation of stem education and teaching activities. The development and implementation path of kindergarten stem educational activities based on data mining algorithm using data technology to realize continuous audit can not only improve the audit means and scope but also provide new research ideas for the expansion and innovation of audit work, which is useful in building a path model of kindergarten stem educational activities development and implementation.
COVID-19 Face Mask Detection

Abstract: Face mask detection involves in detection the placement of the face then crucial whether or not it's a mask thereon or not. the problem is proximately cognate to general object notion to detect the categories of objects. Face identification flatly deals with identifying a particular cluster of entities i.e., Face. it's varied applications, like autonomous driving, education, police work, and so on. This paper presents a simplified approach to serve the above purpose using the basic Machine Learning (ML) packages such as TensorFlow, Keras, OpenCV and Scikit-Learn. The planned technique detects the face from the image properly and so identifies if it's a mask on that or not. As an investigation taskperforming artist, it ought to conjointly sight a face at the side of a mask in motion. The technique perform accuracyup to 95.77% and 94.58% respectively on two different datasets and count optimized values of parameters using the Sequential Convolutional Neural Network model to detect the presence of masks correctly without causing over-fitting. Keywords: TensorFlow, Keras, OpenCV and Scikit- Learn
Practical experience of soft skills formation in students of pedagogical HEIs

Modern policy in the field of higher education determines the strategic directions of vocational education aimed at the needs of society and future employers, including the high quality of training for graduates of HEIs, including future teachers. Most students really think about self-development, but only half build their development trajectory in the process of vocational training. It has been proven that soft skills develop more actively during participation in educational and social activities, since students have the opportunity to constantly develop and improve these skills. The purpose of the article is to substantiate the need for the formation of soft skills in students and the presentation of practical experience in the formation of soft skills during the teaching of academic disciplines in the pedagogical cycle. The article presents approaches to the classification of students' soft skills. The authors of the article consider the ways of organizing activities for the formation of soft skills in students, including practical experience in their formation in the academic disciplines of the pedagogical cycle, as well as during extracurricular work. As the most practiced technologies for the formation and development of soft skills in classroom and extracurricular activities, one can single out: information and communication technologies, technologies for the development of critical thinking, project technologies, technologies for problem-based learning, case technologies, technologies for creating a subject-developing environment, learning technologies in cooperation , technology research activities and traditional technologies.
Identifying Author in Bengali Literature by Bi-LSTM with Attention Mechanism

Authorship Attribution is the task of determining the author of an unknown text using one’s writing patterns. It is a well-established task for high-resource languages like English, but it is challenging for low-resource languages like Bengali. In this paper, we propose a Bi-directional Long Short Term Memory(Bi-LSTM) model with self-attention mechanism to address this problem. GloVe embedding vectors encode the semantic and syntactic knowledge of words, which are then fed into the Bi-LSTM models. Moreover, attention mechanism enhances the model’s ability to learn the complex linguistics patterns through learnable parameters, which gives lower weights to common words and higher weights to keywords that capture an author’s stylistic components. It improves performance extract contextual features. We evaluate our model on multiple datasets and experiment with various architectures. Our proposed model outperforms the state-of-the-art model by 12.14%-20.24% in the BAAD6 author dataset, 1.05% - 7.34% in the BAAD16 author dataset, with best performance accuracy of 97.99%. The experimental results demonstrate that the Bi-LSTM model’s attention mechanism notably boosts performance. (The source code are shared as free tools at https://github.com/IbrahimAlAzhar/AuthorshipAttribution)
Design of a Body Temperature Measurement System applied to Health Center Personnel

COVID19 has left a crisis in the economy around the world, being a highly contagious virus and not having adequate control, it spread through many countries, which is why it was declared a pandemic on March 11th , 2020, by the World Organization of health (WHO). Until the beginning of May 2021, more than 153 million people have been infected and it has caused more than 3.2 million deaths around the world. In Peru, the first case was confirmed on March 6th, 2020, with the number of cases rapidly increasing and the first fatalities appearing on March 19 (three on the same day) and two in the following days. With this, COVID19 made us see how in our country the health system was not prepared to face a problem of such magnitude, therefore, naked the terrible health situation in Peru. In view of this problem, in this article the design of a body temperature measurement system applied to the health center staff was carried out, in such a way that it measures the body temperature of each person who enters the health center, with this, we would have greater control and in addition to helping to avoid spreading the virus that currently continues in our environment. Through the design of the system, it was observed that the system worked in the best way by making the personnel in charge aware of the measurements made by the system. Keywords-- Arduino, Buzzer, COVID-19, Sensors, COVID19, WHO, Peru, Proteu
Recommendation Systems in the Big Data Era

Rapid progression in technology and increasing use of social media platforms like Facebook, Instagram and Twitter has altered the way of articulating people’s judgment, observation and sentiments about specific product, services, and more. This leads to the production and accumulation of massive amount of data. Recommendation systems are getting impetus when it comes to find insights from this data to make decisions that can be represented in various statistical and graphical forms. They have proven useful in predicting or recommending products ranging from food, movies, restaurants etc. This paper presents an overview about recommendation systems and a review of generation of recommendation methods based on categories like contentbased, collaborative, and hybrid approaches. The paper will enlist the limitations which the present recommendation system faces and the possible improvements required in their capabilities to fit into a wider range of application areas.
On the Mapping Problem in SLAM Approaches for Autonomous Robot Navigation

Abstract Simultaneous Localization and Mapping (SLAM) is a well-known strategy for enabling robots to maneuver in unknown environments. The solution to a SLAM problem provides information about the location of the robot and the structure of the environment in a way that enables better decisions to be made by that robot. There are many ways of localizing the robot by using on-board sensors such as ranging sensors, motion sensors, and vision sensors; however, all SLAM methods tend to share features of the mapping strategy. Generally, there are two main mapping methods. One approach augments the coordinates of all landmarks in the environment with the robot pose as one state vector, and the second creates a 2-D or 3-D grid of the environment and then assigns occupancy levels of the landmarks in each grid location. Although both methods have been effective, they have some limitations. The first method is computationally burdensome since increases the size of the state vector whenever landmarks are observed; the second method treats all grid occupancy levels in binary form where all occupied grids are assumed to be at equal levels although certain grids may have occupancies that do not affect the robot mobility. This paper presents a simple but effective grid-based mapping strategy that integrates the path planning step for autonomous ground robotic vehicles. The map is presented as a 2-D surface on which each point is weighted based on observed landmarks and their sizes. This map is updated continuously as new landmarks are detected without changing memory requirements of the robot. The path planning task is implemented by joining points that are on a steep path towards the destination. Preliminary numerical results on its performance on path planning indicate the robot was able to follow the shortest path and the process is not computationally intensive.
Enhancing the Security of Digital Image Encryption using Diagonalize Multidimensional Nonlinear Chaotic System

This paper describes a new efficient cryptosystem for the color image encryption technique, based on a combination of multidimensional proposed chaos systems.This chaos system consists of six bisections: (), (), (), (), (), and () .They induce three chaotic matrix keys and three chaotic vector keys.We use a multidimensional chaotic system together with an encryption algorithm to provide better security and wide key spaces.The proposed cryptosystem uses four levels of random pixel diffusions and permutations simultaneously and -times interchange between rows and columns.The correlations between the RGB components of the plain image are reduced.The level of security, the computational complexity, the quality of decoding a decrypted image under closure threat is improved.The simulation results showed that the algorithm shows a high level of security, and the assurance that the image recovered at the receiving point is identified as the image at the transmission point.
Impact Of The Coronavirus (Covid-19) Pandemic On Education

In 2019, humanity faced a new challenge and threat called the coronavirus pandemic that has been affecting nearly all societal strata worldwide.A number of governmental measures have been taken to counter risks of the disease.These measures included travel restrictions, mandatory travel quarantines, social distancing, bans on public gatherings, closures of schools and other educational institutions, businesses, self-isolation, calls for people to work at home and curfews.The topic is relevant due to the fact that today humanity is struggling with the coronavirus pandemic.Closures of educational institutions in 2020 was a preventive measure to reduce the spread of the pandemic.In this regard, it is necessary to find out how the coronavirus pandemic has affected the education sector.The paper explores the impact of the previously unknown coronavirus pandemic on education.The paper is an account of events highlighting the problems encountered in education because of the spread of COVID-19.Closures of educational institutions had a negative impact on student performance, opportunities for their growth and social development.Not all heads of educational institutions, teaching staff, students, parents were prepared to switch to online learning, many needed to develop their knowledge, skills, and information and communication technologies.This is just a small list of problems that the pandemic has caused in education.Given a long-term prospect of modern society co-existing with the coronavirus, we consider it important to study the effects on the educational environment in-depth in order to minimize their negative impact.
A fast and non-trainable facial recognition system for schools

Deep learning models have been at the forefront of facial recognition because they deliver improved classification accuracy over traditional ones. Regardless, deep learning models require an extensive dataset for training. To significantly cut down on its training time and dataset volume, pretrained models, have been used although, they are still required to undergo the usual training process for custom facial recognition tasks. This research focuses on an improved facial recognition system that lacks the training and retraining requirements. The system uses an existing deep learning feature extraction model. First, a user stands before a camera-enabled system. After that, the user supplies a unique identification number to fetch a corresponding face image from the database. This process generates two face feature vectors. One from the camera and that retrieved from the database. The cosine distance function determines the similarity value of these vectors. When the cosine distance value falls below a set threshold, the face is recognized and access granted. If the cosine distance of the two vectors gives a value above this threshold, access is denied. The proposed model performs satisfactorily on publicly available datasets.
Implementation and Use of Base64 Algorithm in Video File Security

Personal data is often the target of irresponsible people to misuse. The theft is carried out to profit from the person who has the data. In addition to the theft of work files, theft is also carried out on video files. The theft of this file aims to find out what the contents of the video are. Someone has a private video recording that should not be known by others. Misuse of video files will be fatal for the owner of the video. Cryptographic techniques are needed in video security. Caesar Cipher algorithm can help users in securing the video file. The Base64 algorithm can be used to change the ASCII 256 format to Base64 so that it is easy to send or store in a storage media. This algorithm will make the file structure simpler so that it can be displayed and saved. By applying the Base64 algorithm and Caesar Cipher on video files, the security and confidentiality of the files will be guaranteed
Review on The Teaching of Building Materials in Higher Vocational Colleges Based on the “Three Educations” Reformation

Building materials is not only a basic course content of architectural specialization, but also a practical course content taught in higher vocational institutions. It has a large number of knowledge points, a large number of principled and operational contents, and weak logic, all of which have an impact on the teaching effect. It is necessary to strengthen research on higher vocational building materials curriculum against the background of “three educations” reformation, as well as explore curriculum teaching reform strategy in conjunction with the current situation of higher vocational building materials curriculum teaching, in order to cultivate talents of high quality and professional ability.&#x0D;
Pengaruh Media Audio Visual Terhadap Prestasi Belajar Siswa di Madrasah Ibtidaiyah Nurul Ilmi Citeureup Bogor 

&#x0D; &#x0D; This study aims to examine the effect of visual learning media on science learning outcomes for fifth grade students at MI Nurul Falah Citeureup. This research method uses a pre-experimental design. The research sample was 20 students consisting of 13 male students and 7 female students. The data collection technique used pre and post test with t test analysis. The results showed that the application of visual learning media in science subjects could improve student learning outcomes. This is indicated by the average IPA pretest score of 62, while the posttest average score of 83.25. Likewise, the calculation results obtained by t count of 7.04 &gt; t table 2.10, thus t count &gt; t table, it can be concluded that there is a significant influence of visual learning media on science learning outcomes.&#x0D; Keywords: visual learning media, learning achievement, natural science
Components of Adaptive Augmented Reality Model for Heritage Mobile Application

Adaptive augmented reality (AAR) is the latest concept of the augmented reality that responds and adapts to a real-time context and thecharacteristics of the users. This concept is said to provide adaptation of 3Daugmented reality, better engagement and more emotional experience to theusers. In AAR, the information is provided to the users through interaction tracking and sensor on the device. However, this technology is still in itsinfancy. Therefore, a study to explore positive ways of providing relevantinformation that can enhance user experience is urgently required. Theobjective of this paper is to identify the components of an AAR model forheritage mobile application. It is hypothesized that such model would enhance user experience and provide better engagement. Consequently, models from past studies on Augmented Reality, UX Design and storytelling are reviewed. Findings indicate that personalization and emotion are among the important components. Inclusion of these components seems to allow users to be more engaged and inspired to learn about the cultural heritage, hence enhances user experience.