Reviewerly/exHarmony huggingface dataset:
What are the Characteristics of Learners and the Variations of Non-Electronic Learning Media?

Analysis of media needs is crucial before developing a learning media product. This analysis should immediately look at a need in the field and consider the media according to the criteria and characteristics needed, but this is still ruled out and deemed unnecessary. This study aimed to analyze information about special needs analysis on non-electronic media. This research is a quantitative descriptive study using the NVIVO Plus assisted survey method. The sampling selection is a total of 23 schools were obtained consisting of 23 teachers and 230 students. Data collection were carried out through interviews and questionnaires. The results of the study showed that variations in learning media are still not visible due to the various obstacles encountered by teachers. Students want a variety of non-electronic learning media that is interesting, practical, fun, and easy to understand. Some schools still need non-electronic learning media to support the chemistry learning process, one of which is educational game media, modules, and worksheets based on learning model approaches, as well as a combination of the utility of non-electronic and electronic media.
Exploring the Use of Digital Technology in English Language Teaching: Strategies and Methods for Effective Implementation

The globalization of technology, including education, has impacted all facets of life. Therefore, English learning strategies must be studied so teachers can easily choose and determine English learning strategies for teaching students digital base technology. This research aims to describe (1). Digital technology in the world of education; (2). Digital technology-based English learning methods; (3). Digital technology in the development of language learning skills. Hence, this study applied library research methods through gathering research article by utilizing Publish-or-Perish application. The results of this study are (1). Technology supporting education is expected to assist students and educators in carrying out teaching and learning activities in schools; (2). At this time, many English learning methods have been integrated with digital technology. Such as utilizing digital technology using the direct method and others; (3). The use of digital technology is also used in developing students' English skills (listening, speaking, reading, and writing), for example, the use of YouTube videos, digital posters, digital comics, and Grammarly tools. Henceforth, this study urges the ELT teachers to leverage their digital technology competences as well as their pedagogy to attend meaningful and engaging learning for their students.
A Morphosyntactic Analysis on Narrative Writing of the Fresh Year Students’s of Management Informatics AMIK MEDICOM

The purpose of the research is to analyze about morphology and sintactic structure in writing an English narrative essay. Morphology and Sintax are very important studies in learning English. Morphology is the study of how words are structured and how they are put together from smaller part, as morphemes are the smallest significant units of grammar. Meanwhile syntax discusses how sentences are structured. The purposes of this research are to cover the students morphosintactic errors operating on the students of the management informatics students’ narrative writing and how these errors affect the whole clause structure, the inflectional morphemes, derivational morphemes and the pattern of clause structure in the students narrative writing. The method used in this reserch is qualitative describtion where the data sources are taken from the fresh year students narrative writing. The finding revealse are two kinds of morphology, they are derivational and inflectional. Affixes such as suffixes, infixes, prefixes, ablaut and reduplication are kinds of derivational morphology, meanwhile plural, possessive, past time, progressive, comparative, and superlative are kinds of inflectional morphology. Syntactically, the errors occur becuse of not being aware how to build a phrase or a sentence in English. They write more than one verb in a phrase or a sentence which does not need but one. As well they are not sure about word order in English and how to build a simple sentence. They like to miss subject or object pronoun in their sentence. We can explain that by saying that all these forms do not exist in Bahasa Indonesia (Indonesian Language), resulting in the tendency for the students to omit or add these forms in their writing. Too many clauses in one sentence often occur in their sentece.
Visualization of Covid 19 Information in Banten Province Based on Android

Information visualization is a method for delivering information in visual form. Information visualize is vital if information about covid 19 is presented to the public, especially in the Province of Banten. Because the covid-19 virus is still high in the Province of Banten, as well as the lack of information about the spread of the covid-19 virus, there is need for caution so that the number of cases can be suppressed and may not increase. This requires A Covid 19 Information Visualize Android Application To Educate People In The Province Of Banten. So people can find out information about the covid-19 virus case. The application uses waterfall methodology for analysis that will identify the problem, data collection for android based information visualization. The next step is the design to design an android interface system app. Squence diagram, use case, erd (entity relationship diagram), and activity diagram are used for system design diagram. Based on the research from the android based app that will show information's visualization of covid 19.
Inventory Container Information System at PT. Sarana Bandar Nasional

Inventory information system is a collection of procedures that are useful for generating inventory information in the company. The system is required by PT. SBN as a service provider of loading and unloading of container goods. PT. SBN must ensure that the container stock available at the port in each branch continues to meet customer needs. The methodology used in developing this system is the waterfall model. At the requirement stage, researchers conduct interviews to user PT. SBN regarding their needs. Then at the design stage researchers create flowchart, DFD, ERD, and application display design. Researchers create a web-based container inventory information system that can provide container availability information in all branches. Availability information can be obtained from transaction data inputted to the system. Transaction data produces a graph to determine the quantity of output information and the container input from the port. This can help the management to make decisions regarding maximum stock levels and minimum containers at each port. Applications in the form of this final prototype have been demonstrated to the PT. SBN and get a good rating because it can run as needed.
How Can I Help You? The Influence of Situation and Hostile Sexism on Perception of Appropriate Gender of Conversational Agents

Conversational agents (CAs) are increasingly being developed on commercial websites nowadays. We tested in two studies whether gender stereotypes apply to non-gendered CAs. In the first study, participants evaluated whether CAs are expected to display more masculine or feminine characteristics in situations designed to be stereotypically male or female. The sexist attitudes of the respondents were also measured. As predicted, participants perceived that a CA should be more masculine in stereotypically male situations and more feminine in stereotypically female situations. Moreover, we found that hostile sexism but not benevolent sexism moderated the effect of the gendered situation. The second study replicated the results while addressing the limits of Study 1, showing the robustness of these effects. These findings are consistent with models of gender stereotypes in humans and robots and show for the first time a moderation effect of (hostile) sexism in a customer service context with CAs. The processes involved in human relationships seem relevant in a digital environment that involves CAs. Researchers and professionals should work together to avoid reproducing and perpetuating gender stereotypes when developing CAs.
Quantum evolution represented by Brownian motion

We propose a stochastic Schrödinger equation in which the momentum is coupled to a white Gaussian noise. In the stochastic representation, the kinetic energy representing the self-interaction of momentum is reduced to a linear term of momentum. As such, the quantum evolution operator factorizes into two contributions due to the momentum and the potential, respectively. The exact quantum propagator thereby becomes an expectation of the stochastic one in which the amplitude results from the potential with a fluctuating position: The particle moves with a constant velocity, subjected to a complex Brownian motion. We demonstrate that the stochastic Schrödinger equation can be feasibly used to derive the quantum propagators for the linear potential and the harmonic oscillator system. Novel semiclassical and other approximations may be developed from the new representation of quantum mechanics.
Mushroom Image Classification Using C4.5 Algorithm

This study applied five types of Mushrooms, they are Button mushrooms, Wood Ear mushrooms, Straw mushrooms, Reishi mushrooms and Red Oyster mushrooms. The feature extraction used is Order 1 with the parameters of mean, skewness, variance, kurtosis, and entropy. The process carried out to identify mushroom images by preparing image objects. There were 15 images of each mushroom class were taken for each mushroom and stored in .jpg format. The image processing is carried out by a feature extraction process. Then five images for each mushroom class are chosen. They were used as test images which will be classified so that identification results are obtained. This study applies the Classification Algorithm C4.5 to build a decision tree, which will also identify the results of the accuracy of processed mushroom images. The obtained result of accuracy was 84% in the classification of feature extraction Order 1
SAlign: A Graph Neural Attention Framework for Aligning Structurally Heterogeneous Networks

Network alignment techniques that map the same entities across multiple networks assume that the mapping nodes in two different networks have similar attributes and neighborhood proximity. However, real-world networks often violate such assumptions, having diverse attributes and structural properties. Node mapping across such structurally heterogeneous networks remains a challenge. Although capturing the nodes’ entire neighborhood (in low-dimensional embeddings) may help deal with these characteristic differences, the issue of over-smoothing in the representations that come from higherorder learning still remains a major problem. To address the above concerns, we propose SAlign: a supervised graph neural attention framework for aligning structurally heterogeneous networks that learns the correlation of structural properties of mapping nodes using a set of labeled (mapped) anchor nodes. SAlign incorporates nodes’ graphlet information with a novel structure-aware cross-network attention mechanism that transfers the required higher-order structure information across networks. The information exchanged across networks helps in enhancing the expressivity of the graph neural network, thereby handling any potential over-smoothing problem. Extensive experiments on three real datasets demonstrate that SAlign consistently outperforms the state-of-the-art network alignment methods by at least 1.3-8% in terms of accuracy score. The code is available at https://github.com/shruti400/SAlign for reproducibility.
EAS-CNN: automatic design of convolutional neural network for remote sensing images semantic segmentation

Accurate and effective semantic segmentation methods for remote sensing are important for applications such as precision agriculture, urban planning, and disaster monitoring. Convolutional neural networks (CNN) have achieved remarkable performance in the field of remote sensing semantic segmentation. However, the design of CNNs is both time-consuming and necessitates a substantial amount of domain expertise and experience. To address the aforementioned issues, we propose a neural architecture search method called EAS-CNN. The method constructs a search space based on a U-shaped structure and utilizes a fixed-length encoding solution based on gene expression suppression to preserve potential useful information during the evolution process. Furthermore, an improved genetic strategy is proposed to enhance search efficiency and save computational resources. In this paper, we evaluate the proposed EAS-CNN method against state-of-the-art semantic segmentation methods and verify its effectiveness. Experimental results show that EAS-CNN achieves high OA values of 91.2% and 91.6% on the Vaihingen and Postman datasets, respectively. Furthermore, we conduct a thorough analysis of the experimental results and summarize effective design patterns for model architecture to enhance remote sensing semantic segmentation tasks.
STUDENTS’ PERCEPTION OF ONLINE CLASSES IN HIGHER EDUCATION INSTITUTIONS BEFORE AND AFTER THE EMERGENCE OF COVID-19 IN BOSNIA AND HERZEGOVINA

The year 2020, apart from the Covid-19 pandemic, was also marked by a way of learning in higher education institutions that had not been applied to a large extent until then -online learning.At the beginning of 2020, due to the circumstances caused by the aforementioned pandemic, universities in Bosnia and Herzegovina were forced to switch to an online form of teaching in order to maintain continuity in work and learning.Such a way of learning required students' computer literacy, which has become one of the basic conditions in modern education.High-quality participation of students in classes meant, in addition to communication with professors and each other, the use of available sources of information necessary for the learning process.This research deals with students' perception of online classes before and after the outbreak of the Covid-19 pandemic as one of the key components of the process of identifying online classes' success.The survey was created in the 1KA survey platform and carried out between November 15, 2021 and January 15, 2022 in Bosnia and Herzegovina.
A descriptive analysis of digital game-based foreign language education

Digital games are increasingly being used for foreign language learning; a trend that has grown popular recently.This research dives deeply into this topic, assessing different skill areas targeted by these digital games, and how they are utilized in various settings worldwide -educational and otherwise.The research takes into account studies carried out between 2010 and 2021.The study's methodology is rooted in qualitative research, specifically the embedded theory design, and the gathered data is interpreted through a descriptive analysis approach.Out of an initial pool of 145 academic studies reviewed, 57 met the necessary criteria for inclusion, such as quality of data, sample size, year of publication, gender balance, and content relevance.The analyzed data is then expressed in terms of frequency and percentages for simplicity and easier understanding.The findings show that studies focusing on the use of digital games for foreign language learning have multiplied in recent years.However, a large proportion of these studies are heavily focused on vocabulary acquisition.This led to the suggestion that future work in this area should broaden its scope to include other important language skills like reading, writing, and listening, in addition to vocabulary.
Book Marketing in Nigeria: Appraising the Role of Digital and Social Media Innovations

Nigeria’s huge population assures a ready market for books, setting the stage for a virile book publishing industry. However, the book industry has been characterized by some anomalies, including the shortage of tertiary level textbooks and the non-availability of books in professional fields like medicine, engineering and technology. Although the situation has improved considerably over the years, the emergence of digital technologies has set the tone for competition in consumer media markets, with book publishers struggling to gain competitive advantage through digital media adoption. Past studies record various approaches to repositioning the Nigerian book publishing industry for growth and development through the adoption of various forms of digital publishing innovations. However, there is a knowledge gap on the role of social media innovations in the prevailing business-to-consumer (b2c) book market environment in Nigeria. A review of extant literature reveals that the book market in Nigeria has been greatly influenced by the demand for educational materials, especially textbooks for primary and secondary level education. It is established that to expand and grow a virile book publishing industry, Nigerian publishers need to open up new book markets and deploy digital and social media innovations to attract new customers, develop relationships, and increase awareness.
Dot Voting Technique to Improve Narrative Text Writing Skill of the Eighth Graders

Writing used to express and to communicate some ideas. The score of students’ narrative writing skill of eighth graders of one state junior high school in Semarang is under of minimum criteria. The English standard minimum score is 75. Objectives of this research are to know how great Dot Voting technique can improve students’ eighth graders learning motivation in class and to know how high Dot Voting technique increasement of students’ narrative writing skill at the eighth graders of one state junior high school in Semarang. Classroom action research is the research type. The research was conducted in class VIII D of one state junior high school in Semarang. This research used non-test and test instruments to collect the data. The non-test instruments are observation sheet and documentation. The writer used quantitative data in analyzing the data. In first cycle and second cycle, the students have better enthusiasm and participation to follow the activities. At pre-cycle test, their writing average score reached 65.74. In first cycle test when the writer applied the action the students’ writing average score is 74.87 or improves 9.13. In second cycle test, their writing average score reaches 82.09. It means that it improves 7.22 from the first cycle. In second cycle indicates that the teaching process is successful. Based on the result, firstly, to English teachers to use interesting teaching technique in teaching especially in writing skill is Dot Voting technique. Secondly, to students to enrich their narrative text writing skill by using Dot Voting.
Cryptographic Method to Enhance the Data Security using ElGamal Algorithm and Sumudu Transform

Abstract: Cryptography is the science of using mathematics to encrypt and decrypt data. Cryptography includes two phases: Encryption and Decryption. Encryption is the process of transforming plaintext to ciphertext, whereas decryption is the reverse procedure. Encryption and decryption schemes based on Sumudu Transform are unable to give more security while communicating the information. ElGamal is a public key algorithm that is based on the discrete logarithm problem. The purpose of this study is to introduce a cryptographic method that uses the ElGamal algorithm and Sumudu Transform to improve communication security.
Estimation of Actual Evapotranspiration (ETa) of Major Crops of a Distributary of Mahanadi Canal Command Using CROPWAT 8.0 Model by Penman: Montieth Method

This paper aims to estimate Actual Evapotranspiration of major crops by using CROPWAT 8.0 software in 2A canal command of Mahanadi of Dhamtari district. Actual evapotranspiration is a key process of hydrological cycle and a sole term that links land surface water balance and land surface energy balance. Irrigation is an essential part of different crops because rainfall is not enough for irrigated farmland. Long term daily meteorological data including rainfall, maximum temperature, minimum temperature, relative humidity, wind speed and sunshine hours of IMD station data was used as input data in modified Penman method and CROPWAT 8.0 model. The crop stage data, including the value of Kc in, Kc mid, Kc end for the selected crop was obtained from Department of Irrigation the rooting depth, critical depletion and crop height of different crops are taken from FAO Irrigation and Drainage Paper 56. The Penman Monteith method was used to estimate ETo and ETc respectively. The major crops in 2A canal command area are Paddy, Wheat, Chickpea , Summer Paddy. Based on the intensive study of this paper, daily basis meteorological weather data was recorded from 2007 to 2021 were used to obtain the result. The study detects that Penman–Montieth method is the best method to estimate Actual Evapotranspiration of all crops.
Optimal Geometry and Motion Coordination for Multisensor Target Tracking with Bearings-Only Measurements

This paper focuses on the optimal geometry and motion coordination problem of mobile bearings-only sensors for improving target tracking performance. A general optimal sensor–target geometry is derived with uniform sensor–target distance using D-optimality for arbitrary n (n≥2) bearings-only sensors. The optimal geometry is characterized by the partition cases dividing n into the sum of integers no less than two. Then, a motion coordination method is developed to steer the sensors to reach the circular radius orbit (CRO) around the target with a minimum sensor–target distance and move with a circular formation. The sensors are first driven to approach the target directly when outside the CRO. When the sensor reaches the CRO, they are then allocated to different subsets according to the partition cases through matching the optimal geometry. The sensor motion is optimized under constraints to achieve the matched optimal geometry by minimizing the sum of the distance traveled by the sensors. Finally, two illustrative examples are used to demonstrate the effectiveness of the proposed approach.
IMPLEMENTATION OF A COHESIVE STUDENT END RESULT MANAGER

The advanced turn of events and the effect of personal computers and the Web on our lives have been a beneficial to civilization. Higher institutions examinations are performed with broad human intercession physically, the results are produced through a bookkeeping page application and afterward imprinted on a paper, appended to a board for the assertion, and afterward put away. Due to the increasing number of students in recent years and some human limitations, lots of problems have been encountered in area of Students registering of coursewhich are not included in the program which they study, omitting carry-over courses during result compilation, students offering more or less credit load than required and lack of adequate guidance in course registration. This research aims at making a web-based cohesive student result management system for higher institutions to lessening the time, effort, and improving the security of compilation of results by designing and implementation of the database, user-based interface, user access privilege and business logic. The strategy received for the elaboration of the venture depends on the subjective study. The functional result management system was developed using Django as the template and HTML and CSS as the view. The database used in iSRM (the student result management system) was designed with SQLite Database Management System (DBMS) which serves as the model