Reviewerly/exHarmony huggingface dataset:
Implementation Of The Genre Model In The Internet Forum

The virtualization of social reality, mediated by Internet technologies, significantly transforms, turns it into a new, previously non-existent reality. Virtual discourse requires special attention, which implies thorough examination of various linguistic features: morphological, syntactical, lexical, textual, and communicative. The possibility of applying the notions of a genre and a generic classification with respect to virtual discourse is in the focus of the present paper. In accordance with one of the linguistic convictions, no piece of speech is produced as genre-independent. People belonging to any socio-cultural community develop characteristically patterned ways of language use. Different non-virtual spheres of human communication or discourses as their linguistic correlates are generically stratified. Systemic-functional theory of language treats genres as social constructs facilitating human interaction. The present paper is concerned with a communicative pragmatic genre model comprising five constituent members. These constituent members may be present in texts of any genre, but their composition and configuration vary. In order to give answers to the question whether the Internet communicative space can be seen as genre-dependent, the Internet forum, one of the Internet communication tools, is being looked into through the prism of a five-member model. The obtained results are being discussed against the background of traditional non-virtual spheres of language use.
SECONDARY SCHOOL STUDENTS’ EXPERIENCE IN RECIPROCAL TEACHING STRATEGY ON READING COMPREHENSION THROUGH THE FLIPPED CLASSROOM

This study reports a qualitative research micro ethnographic study on Secondary School Students Experience in Reciprocal Teaching Strategy on Reading Comprehension through the Flipped Classroom. One research question will guide this study: What is the students' experience in Reciprocal Teaching Strategy on Reading Comprehension through the Flipped Classroom? The participants of this study were five students of secondary school. This research was conducted at one of the secondary school in West Java, Indonesia. The data used this study are semi-structural interview techniques. The data analysis uses Thematic Analysis of Braun and Clarke (2006), which consists of 6 stages, namely the stage of familiarizing with the data, generating initial code, searching for themes, reviewing themes, defining and naming themes, and producing the report. The findings report that learning reading comprehension using reciprocal teaching strategies with the flipped classroom method can encourage students' interest in remembering and developing a new vocabulary that they do not know. Furthermore, learning reading comprehension using reciprocal teaching strategies with the flipped classroom method involves students learning collaboratively, expanding their reading skills. Finally, the finding shows that learning reading comprehension using the reciprocal teaching strategy with the flipped classroom engages students in reading activities and this activities can help students understand recount texts. Keywords: Reciprocal Teaching strategy, Reading Comprehension, The Flipped Classroom, Students Experience
Visibility Analysis Based on Deep Learning

In recent years, visibility analysis through deep learning processing and analysis of video images for different places has become a hot research topic that attracts people's attention.A new deep learning model (A-VGGNet) is proposed to evaluate the visibility of real scenes.The model is constructed on the basis of the VGG classification model, and the classification accuracy of the deep learning model is improved by adding an attention mechanism.The experimental results show that the training success rate is 97.62%, the verification set test accuracy rate is 75.05%, and the test set classification accuracy rate is 85.05%.The proposed model has a good effect on the accuracy evaluation and classification of visibility.
Computer Science Education, Zone Of Proximal Development For Primary School Pupils

It is currently under discussion the imminent digitalization strategy of education in Romania.Our interest was to collect a set of indicators of the skills and motivations expressed by the first grade pupils in the interaction with digital and which also reflect a level of development on this dimension.These data, related to other international curricular approaches, could be an argument or a future vision on the depth and organization of content, on in-depth levels, so that they can be delivered at the level of Romanian primary education through computer science education.Indicators of the presence of pupil digital skills, as input in primary education, were considered in relation with the current zone of actual development (ZAD), reflecting the potential and premises for developing an elementary level of digital competence, as output and zone of proximal development (ZPD) in primary education.These aspects of micro-research, together with theoretical considerations, advise us to place computer science education in the zone of proximal development for primary school students.The data were collected through the opinion of the parents of first grade pupils, who played the role of learning partners of their children, in a school semester conducted online, under the restrictions marked by the Covid-19 pandemic.
A grammatical investigation of possessive cases in English and Okpameri

Possessive cases are words that indicate or show possession. Hence, “hers”, “her” and “Ojo’s” are some examples of possessive cases. These possessive cases indicate grammatical property of language. The usage of these cases in utterance varies in languages. Hence, they variations often pose problem to ESL learners. Predicating on Contrastive Analysis Theory, the study generated Okpameri data from oral sources and participatory observation of the researchers in natural Setting. English data were got from the English grammar texts. The areas of investigation were Possessive Pronouns, Possessive Adjectives and Possessive Nouns. From the findings, the two languages under study are grammatically marked for possessive cases with reference to 1st, 2nd and 3rd person singular and plural numbers. However, the usage of these cases differs. While English is gender sensitive, this is not so in Okpameri language as Okpameri resorts to using uni-gender to indicate possession. Okpameri possessive pronouns and adjectives have different morphological forms representing persons (e.g 1st person singular). Not all forms of possessive cases are capable of co- occuring with every noun. While Okpameri distinguishes between subject and complement possessive cases, this is not so in English. The study, therefore, suggests that language teachers, particularly, English language experts should adopt systematic approach to the teaching of possessive cases as this will further broaden the Okpameri ESL learners’ knowledge on how to use the English possessive cases.
TEACHING ONLINE REQUIRES TEACHER ADAPTABILITY. UPDATING THE TRADITIONAL TEACHER COMPETENCY MODEL

V.M. Cojocariu, E. Nechita, V. Zichil , C. Crişan, C. Grigoras, C. Cîrtiţă-Buzoianu "Vasile Alecsandri" University of Bacau (ROMANIA)
A Visual Measurement Algorithm of Approaching Vehicle Speed Based on Deep Learning

With the urbanizational process expediting and the national economy developing rapidly and healthily, the amount of private cars is on the rise, and traffic accidents occur frequently due to speeding and other reasons, and the difficulty of traffic supervision has also increased.This topic will use semantic segmentation and feature extraction and matching.Based on the video data of the traffic surveillance camera, an algorithm is designed to quickly calculate the matching of feature points in adjacent frames with low computing power to achieve the calculation.The same vehicle moves within the two frames of the target, so as to calculate the speed of the vehicle.Firstly, performing semantic segmentation based on deep learning, we choose a fully convolutional network to achieve semantic segmentation of depth maps, and distinguish the picture's principal part.After that, we can realize features extraction and mapping.The HOG algorithm is used on the matching step, the target's relative movement is calculated based on these matched point pairs to measure the moving speed of the vehicle.The experiment and the test prove that the system can realize the efficient speed measurement of moving vehicles.
Text difficulty vs text readability: Students� voices

Reading is an essential skill to be mastered, especially by university students and it is the lecturers� responsibility to train their students to develop their reading skill. In order to do so, lecturers will have to develop materials or choose materials from existing books to be used in the teaching learning process. The text difficulty must be appropriate to the students� English proficiency level. This study was aimed at finding the students� perceptions of the difficulty of the texts used in the reading class and the corresponding text readability. This study utilized the survey design and the content analysis involving 141 second semester students of the English Language Education Department of a state university. Questionnaires were used to get data on students� perceptions of the text difficulty and the text readability was analysed with the help of https://readabilityformulas.com. The data on students� perceptions were analysed using percentage while the data on the text readability were analysed using the readability test. The findings showed that there was a difference in the students� perception of the difficulty of the text and the readability level as being calculated using different readability formulas.�
COMPARING ANTIBODY TITERS AFTER VACCINATION IN DOGS USING ELISA READER WITH IMAGE PROCESSING TECHNIQUES

Rabies is a zoonotic diseases that is caused by a virus of the genus Lyssa virus that attacks the central nervous system (CNS) and is transmitted through the bite of Rabies Transmitting Animals, especially dogs. Rabies can be prevented but is always fatal in humans if it infects the Central Nervous System (CNS). Vaccination has been used as one of the rabies prevention programs. A total of 83 samples were tested using Indirect ELISA (Enzyme-Linked Immunosorbent Assay) to identify antibody titers after rabies vaccination. Antibody titer correlated with absorbance value and concentration of standard solution. The absorbance value was read by ELISA reader and desktop scanner. The absorbance values were read at 450 nm and 620 nm as a reference using an ELISA reader and images from a desktop scanner were processed using the ImageJ application. The purpose of this study was to compare the obtained results using an ELISA reader as the gold standard and scanner images processed using ImageJ including sensitivity, specificity, and accuracy. There is no significant difference between the ELISA reader as the gold standard and alternative test equipment. The desktop scanner has a sensitivity of 97%, a specificity of 88.8% and an accuracy of 96%. The absorbance measurement method using an ELISA reader is expensive and difficult relatively to carry out in a laboratory with minimum financial support so that the image from desktop scanner processed using the ImageJ application is expected to be an alternative choice for an ELISA (Enzyme-Linked Immunosorbent Assay).
Richards Curve Implementation For Prediction of Covid-19 Spread in Maluku Province

COVID-19 (Coronavirus Disease 2019) was first reported in Wuhan city, China at the end of December 2019 and spread to Indonesia specifically in Maluku Province at the end of March 2020. This study aims to predict the spread of COVID-19 cases in Maluku province as well as explore the phases of its spread using the Richards Curve which is an extension of the Logistic Curve. After estimating the parameters of the Richards Function with cumulative case data of COVID-19 in Maluku province from March 23 to November 4, 2020, the results of the spread of COVID-19 cases in Maluku province reached a turning point on October 22, 2020, and ended on May 25, 2023, with a total cumulative case of 9,451 cases
Online Auction System

Aims: In today’s world everything is going online which effects market that are offline. Auction of any rare products are bid offline, but it’s time to push this auction system online so that more buyer’s will connect online and more bid options will available for them. Online auctions are the most influential e-commerce business applications. Although there have been considerable efforts in setting up market places, online trading still lays in its early stages. Online auction system is the best way to bid such a products who are rare and can’t find easily anywhere. This is mostly work for archaeological old products that are rare. Methods: The most impressing concept of online auction system is you don’t need to anywhere offline. It’s the system where you can bid online without investing your time and bid for particular products. Results: Using this system buyers, sellers come online and connect on web-portal using this system. Conclusion: In this system using this web- portal registered user can propose or bid for new auctions, purchase and place bid product in order to buy that item.
APPLICATION OF CONTINUOUS WAVELET TRANSFORM IN THE ANALYSIS OF ELECTROCARDIOGRAM SIGNALS

The electrocardiogram is known as a primary and powerful diagnostic tool that provides all essential information about the health of our heart.The feature extraction of electrocardiogram, such as R-peak detection, is the central core of any electrocardiogram analysis.Study of electrocardiogram in wavelet domain using continuous wavelet transform with well-known wavelets and other proposed wavelets for this investigation is found to be helpful and yields reasonably reliable results.In order to validate this method, we apply it to several MIT-BIH database records.The continuous wavelet transform with one of the proposed wavelets namely, Mxr-1, achieves 99.97 % sensitivity, 99.89 % positive predictivity, and 0.135 % detection error for accurate detection of R peaks in comparison with the well-known standard wavelets such as Morlet, Mexican hat and Daubechies 4 and two other proposed mother wavelets Mxr-2 and Mxr-3.
Sparsity-Aware Reachability Computation for Massive Graphs

We propose a novel sparsity-aware reachability computation framework so-called S-AORM, which provides fast performance for massive graphs via incremental fashion using sparse matrices. S-AORM is straightforward to compre-hend and outperforms existing methods in terms of compu-tational performance. Five synthetic networks generated from Barabási-Albert model and five real-world networks are used in comprehensive experiments. In terms of all-pairs shortest paths computation performance on the citation network, which is a directed and disconnected network, the proposed approach surpasses SNAP by up to 12.1 times and NetworkX by up to 80.2 times. The overall experimental results demonstrate that our approach provides significant performance improvement in the graph reachability computation.
THE STUDY ON CODE SWITCHING AND CODE MIXING IN ENGLISH TEACHING AND LEARNING PROCESS AT VIII 2 GRADE MTsN 2 SOLOK SELETAN

This research aims to determine the types of code switching and code mixing used by teachers in schools. This study uses descriptive qualitative research. In data analysis, researchers used instruments such as observation, interview and recording. The population of this study is the teacher and students of class VIII 2 MTsN 2 Solok Selatan. The results of the investigation is about how there are two language in the bilingual class : Indonesian as the main language and English as an additional language. The researchers found that there of code switching carried out by English teacher in the classroom according to theory, namely the type of Tag switching , Intra-Sentential switching and Inter-Sentential switching. According to the theory, the code mixing is divided into three types according to theory, Insertion, Alternation and Congruent Lexicalization. In research results , code switching often use intra sentential switching, and code mixing which is often used in the classroom is alternation. The conclusion of this discussion is that code switching and code mixing
XNPU - eXtensible Neural Processing Unity From a Programmable Logic Device

As an emerging field of machine learning, deep learning represents a powerful technique to solve complex learning problems. However, the size of the networks becomes increasingly large due to the demands of the practical applications, which poses a significant challenge to construct high-performance implementations of deep learning neural networks. In order to improve the performance as well as to maintain the low power cost, in this paper we design a neural processing unit, which is a scalable accelerator architecture for large-scale deep learning networks using the Field-Programmable Gate Array (FPGA) as the hardware prototype.
Machine Learning Techniques for Solving Constrained Engineering Problems

This paper focuses on the application of the supervised machine learning technique. The main objective is to construct models of objective functions. Sixteen different varieties of benchmark test functions and three well-known engineering design problems are evaluated by machine learning technique. The Artificial Neural Networks (ANNs) technique is used for constructing models. For the sake of accuracy check, three metrics are used; Mean Square Error (MSE), Root Mean Square Error (RMSE) and Maximum Absolute Error (MAE).
DIGITALIZED RISK MANAGEMENT IN TEACHING – EVALUATION OF THE COMPETENCE DEVELOPMENT OF STUDENTS BY INTRODUCING A RISK MANAGEMENT TOOL

Digitalization of business processes in companies provides the basis for innovation and ensures survival on the market. With a particular focus on risk management, the digital transformation in companies is producing new sources of information such as big data and will allow companies to identify and monitor risks in near real time in the future. In order for the risk management function to be able to cope with this transformation task, it is necessary to take up suitable risk management tools in teaching and implement them appropriately.In the context of a course in the specialization Risk Management, practical teaching content was previously taught using a spreadsheet program. In order to take development of digitalization into account, we decided to switch from this spreadsheet-based teaching approach to the use of a risk management software also used in companies. In this way, digital transformation also takes place in teaching at the university. In this article, we look at the changeover of the event from different perspectives, because the use of the software not only influences the structure and content of the course but also learning objectives and competencies. On the one hand, we will present the challenges and opportunities that the introduction of the software brings with it from the perspective of the teachers. On the other hand, we will address the experiences of the students who are now using this system in the course. In this context, particular attention will be paid to the impact on the competencies taught.
Differences in the Determinants of National Reserves across G7 and Rising Power Countries

The article investigates the macroeconomic factors influencing national reserves in G7 and Rising Power countries. Factors that have been demonstrated and theoretically explained by many empirical investigations were used in the study. Two distinct panel data analyses were used with a half-century-old data collection for this aim. For each nation group, four distinct specifications have been developed. Both the System-GMM method, which is one of the dynamic panel data methodologies, and the Fixed Effects method were used to estimate the generated specifications. Robustness was applied to the coefficients produced in terms of consistency by employing other variables such as external debt crisis, population, exchange rate regime, and exchange rate crisis. As a result, it is concluded that FDI and deposit interest rates have a negative influence on national reserves in G7 countries while having a beneficial effect for Rising Power countries.
Content Classification based-on Latent Semantic Analysis and Support Vector Machine (LSA-SVM)

The diversity of the content of a web page can have a negative impact if used by the wrong user. Almost a half of internet users are children. Therefore, it is important to classify web pages to find out which pages are worthy of being seen by children and that are not feasible. One method that can be used is the Support Vector Machine (SVM) algorithm. SVM is a binary classification whose working principle is to find the best hyperplane to separate the two classes. To obtain better classification accuracy, the SVM is combined with the Latent Semantic Analysis (LSA) algorithm. The data used in this study were taken from the DMOZ web data which has been classified into two categories. The data is then entered into the pre-processing stage for further feature extraction using LSA. The LSA algorithm is used to find out the semantic similarities of words and text contained in web pages. The results of feature extraction are then classified using SVM with RBF kernel. Based on the testing result, we obtain a classification accuracy of 64%.
THE NEED ANALYSIS OF ETHNOSCIENCE – BASED ENGLISH LEARNING MATERIAL: A CONTEXTUAL MODEL

English is very important for students because English has become one of the International language used by many people. However some obstacles are usually faced by Indonesians who want to learn English. One of the causes of difficulties in learning English is that the material taught is not in accordance with the application of students' daily lives. Analyze the need for ethno science-based English material in contextual model in English subjects was the research purpose. Using the research instrument composed of questionnaire; data were gathered from seventy of the seventh grade students and three teachers of SMPN 14 Semarang to analyze the students and teachers’ needs in learning English. Descriptive statistics were used to analyzed the data. Based from the result, that students and teachers need interesting material in learning and teaching English subject. They agree of developing ethno science-based English material in contextual model because a English subjectis not only theory but need to practice it through student activities. The material better is if it is related to everyday life and the culture values of the local community
Application of a Photoacoustic Tomography System: A Case Study on the Monitoring of Pig Tissue Decomposition

Pig carcasses have been used in forensic research because they share several similarities to human cadaver, including decomposition.In several studies, the decomposition of pig's cadaver for a certain time can be used as a model to determine the time of death of a human.This study was conducted to determine the relationship between the days of spoilage of pig tissue and the level of average sound intensity produced by the sample.Then, in this study, pig skeletal muscles were allowed to decay with a variation of 1-5 days.Afterward, these muscles were imaged using diode laserbased photoacoustic tomography.Results of the experiment show that the average acoustic intensity level from the first day until the fourth day has increased (78-92 a.u for young pig and 76-86 a.u for old pig) but decreased on the fifth day (88 a.u for young and 84 a.u for old pig).These results can improve forensic imaging because such results can be applied to determine the time of death of human by plotting the ratio of the average sound intensity level of the sample to the number of days of decomposition.