Reviewerly/exHarmony huggingface dataset:
Cloud-based cross-platform collaborative augmented reality in flutter

Augmented Reality (AR) as a technology in the business area is utilized in new frontiers such as collaborative real-time experiences and cloud-based solutions. However, there is still a strong tendency towards game engines, which hinders widespread adoption for businesses. We present a collaborative AR framework (Flutter plugin) aimed at lowering the entry barriers and operating expenses of AR applications. A cross-platform and cloud-based solution combined with a web-based content management system (cloud) is a powerful tool for non-technical staff to take over operational tasks such as providing 3D models or moderating community annotations. To achieve cross-platform support, the AR Flutter plugin builds upon ARCore (Android) and ARKit (iOS) and unifies the two frameworks using an abstraction layer written in Dart. In this extensive description we present an in-depth summary of the concepts to realize the framework and prove its performance being on the same level as the native AR frameworks. This includes application-level metrics like CPU and RAM consumption and tracking-level qualities such as keyframes per second used by the underlying SLAM algorithm, detected feature points, and area of tracked planes. Our contribution closes a gap in today’s technological landscape by providing an AR framework with the familiar development process of cross-platform apps. Building upon on a content management system (cloud) and AR can be a game changer to achieve business objectives, while being not restrained to stand-alone single-purpose apps. This will trigger a potential paradigm shift for previously complex-to-realize applications relying on AR, e.g., in production and planning. The AR Flutter plugin is fully open-source, the code can be found at: https://github.com/CariusLars/ar_flutter_plugin .
The Use of Chunking Strategy in Teaching Reading Comprehension

This research was aimed to find out whether using chunking strategy was effective in teaching reading comprehension. In this case, the researcher used quantitative data approach by using experimental design. There were two classes at ninth grade of SMPN 1 Nisam North Aceh as the sample of this research. There were class IX/3 as experimental consist of 24 students and IX/2 as control group consist of 22 students. In experimental group, the researcher used chunking strategy in teaching reading comprehension. After teaching learning process for three meetings, the researcher gave post-test. The result was shown that the students’ achievement in experimental group was higher than control group. It was proved by the average score from pre-test of experimental group was 66,8 and control group was 64,5. Furthermore, the result of post-test of experimental group was 83,2 and control group was 70,3. It could be concluded that using chunking strategy was effective in teaching reading comprehension.
MixLoss: A Data Augmentation Method for Sequence Generation Tasks

Abstract In this paper, we propose MixLoss, a simple and effective data augmentation method for sequence generation tasks like machine translation, speech recognition, etc. MixLoss works by mixing two inputs and two losses with two corresponding outputs using the same weights, which can also be applied in the hidden space. Concretely, when the loss takes the certain form that we define, we prove that MixLoss is theoretically equivalent to Mixup and thus has an adequate theoretical foundation. We corroborate our theoretical analysis with experiments that support our conclusions. Experimental results on the English-Germany dataset reveal that MixLoss achieves the best performance compared with other data augmentation methods, and can integrate well with other technologies. Specifically, the BLEU can be improved from 27.10 to 28.41 on the MT task, and the WER can be decreased from 18.9% to 15.1% on the ASR task. Moreover, MixLoss has stronger robustness to resist noisy data.
Gambaran Pola Asuh Orangtua dalam kaitannya dengan Motivasi Belajar Anak

The purpose of this study was to obtain an overview of parenting related to children's learning motivation, the type of parenting that is effective in motivating children's learning, and to know the role of parenting in influencing children's learning motivation. This study uses a qualitative approach, with 5 children and 5 parents as research subjects. Collecting data using observation, interviews, and other complementary data. The results of the study in the form of parenting and parental participation have an effect on children's learning motivation. Children with democratic parenting have good and sufficient motivation to learn. Children with permissive parenting have less motivation. The application of good parenting can be realized through treatment, attention, fulfillment of needs, and attitudes of parents. The appropriate treatment is in educating children, which will later make it easier to increase children's motivation when learning.
Pengaruh Model Example non Example dalam Pembelajaran Keterampilan Menulis Teks Deskripsi Siswa Kelas VII UPT SMP Negeri 1 Air Putih Kabupaten Batu Bara

This study aims to determine the effect of the example non example model in learning descriptive text writing skills for class VII students of UPT SMP Negeri 1 Air Putih, Batu Bara Regency. In this study using a quantitative method with the type of Pre-Experimental Design using a one-group pretest-posttest design. The sampling used in this research is purposive sampling technique. The data collection technique used is a descriptive text writing test. The results of the research on writing descriptive text before using the example non example model reached an average value of 50.78 in the less category. Meanwhile, the results of the study of writing descriptive text after using the example non example model reached an average value of 72.5 in the good category. Based on the results of the pre-test and post-test, there is an effect on the results of writing descriptive text with tcount 5.19. At a significant level of 0.05 (95% confidence level) with df = 31 obtained ttable = 1.69; significant at p &lt; 0.05. Thus H0 is rejected. With the rejection of H0 then Ha is accepted, meaning that there is a significant influence on the writing skills of the seventh grade students of SMP Negeri 1 Air Putih, Batu Bara Regency using the non-example model.
Pengaruh Model Pembelajaran Treffinger terhadap Kemampuan Menulis Teks Laporan Hasil Observasi pada Siswa Kelas VII di SMP Negeri 2 Tapian Dolok

This study aims to determine: (1) the ability to write a text report on the results of observations in class VII students at SMP Negeri 2 Tapian Dolok before using the Treffinger learning model, (2) the ability to write a text report on the results of observations in class VII students at SMP Negeri 2 Tapian Dolok. after using the Treffinger model and, (3) to find out whether there is an effect using the Treffinger learning model in writing a report text on the results of observations of class VII students at SMP Negeri 2 Tapian Dolok. This research uses quantitative research using experimental methods, while the method used in this research is Pre-Experimental Design (non-design). According to Sugiyono (2019:112) that the results of Pre-Experimental research are independent variables. This happens, because there is no control variable, and the sample is not chosen at random. This study also uses the One-Group Pretest-Posttest Design. The results of this study include: (1) The results of the initial test ability (pre-test) in the skills of writing report texts on the observations of class VII-4 students of SMP Negeri 2 Tapian Dolok before the treffinger learning model is applied, the average value is 39.66 with a total 1.190 From the results (pre-test) obtained by students that the ability to write text reports on observations has not reached the KKM target (Minimum Completeness Criteria) which is 70. (2) The results of the final test (post-test) ability in writing report text skills on class observations VII-4 SMP Negeri 2 Tapian Dolok after applying the treffinger learning model, the average score was 76.96 with a total score of 2.309. From the results (post-test) obtained by students in writing the text of the report on the observation results, they have reached the KKM target (Minimum Completeness Criteria) which is 70. (3) The analysis has been carried out and has been tested statistically that tcount is greater than ttable (9,34&gt;1.699) then causes H0 to be rejected and Ha to be accepted. Thus, it can be concluded that there is an effect of the treffinger learning model on the ability to write text reports on observations in class VII-4 of SMP Negeri 2 Tapian Dolok.
Pengaruh Model Pembelajaran Contextual Teaching and Learning (CTL) terhadap Kemampuan Menulis Teks Eksplanasi oleh Siswa Kelas VII di SMP Negeri 2 Tapian Dolok

This study aims to determine: (1) the ability to write explanatory texts in class VIII students at SMP Negeri 2 Tapian Dolok before using Contextual Teaching and Learning (CTL) learning. (2) The ability to write explanatory texts for students of SMP Negeri 2 Tapian Dolok after the Contextual Teaching and Learning (CTL) model. (3) The effect of using the Contextual Teaching and Learning (CTL) learning model on the ability to write explanatory texts by class VIII students at SMP Negeri 2 Tapian Dolok. This research uses quantitative research. The method used is an experimental method while the method used in this research is Pre-Experimental Design (non-design). According to Sugiyono (2019:112) that the results of Pre-Experimental research are independent variables. This happened, because there were no control variables, and the sample was not chosen at random, this study used a One-Group Pretest-Posttest Design. The results of this study include: (1) The results of the initial test ability (pre-test) in the skills of writing explanatory texts for class VIII-5 students of SMP Negeri 2 Tapian Dolok before the Contextual Teaching and Learning (CTL) model is obtained an average value of 60. From the results of the pre-test showed that the students' ability to write explanatory texts had not yet reached the KKM target of 70. (2) The results of the final test (post-test) skills in writing explanatory texts for students of class VIII-5 SMP Negeri 2 Tapian Dolok after applying the Contextual model Teaching and Learning (CTL) obtained an average value of 70.38. From the post-test results obtained that the students' ability to write explanatory texts has reached the KKM target of 70. (3) The analysis that has been carried out and has been tested statistically that tcount is greater than ttable (3.38 &gt; 2.042) causes H0 to be rejected and Ha received. Thus, it can be concluded that there is an effect of the Contextual Teaching and Learning (CTL) model on the skills of writing explanatory texts by grade VIII-5 students of SMP Negeri 2 Tapian Dolok.
Pengaruh Model Pembelajaran Kontekstual terhadap Keterampilan Menulis Teks Eksposisi Siswa Kelas VIII SMP Negeri 1 Hutabayuraja

This study aims to describe the ability of students in writing exposition texts before and after using the contextual learning model in class VIII of SMP Negeri 1 Hutabayuraja. The method used in this research is the experimental method, and the population in this study are all students of SMP Negeri 1 Hutabayuraja and the sample in this study is class VIII-1 students. In testing the hypothesis, the T test was used. The calculation results obtained tcount &gt; ttable at the level of p &lt; 0.05. Based on the data processing of the ability to write expository texts for the initial test (pre-test) and the final test (post-test), it was obtained that tcount = -11.417. At a significant level of 0.05 (95% confidence level) with a df of 30 obtained ttable = 2.042, significant at p &lt;0.05. Thus, H0 is rejected and Ha is accepted. With the rejection of H0, there is a significant difference in the ability to write exposition texts for class VIII students of SMP Negeri 1 Hutabayuraja.
Pengaruh Metode Diskusi Kelompok dalam Pembelajaran Menulis Teks Berita oleh Siswa Kelas VIII SMP Negeri 7 Pematangsiantar

This study aims to determine: (1) the ability of students to write news texts before using the group discussion method in class VIII of SMP Negeri 7 Pematangsiantar, (2) the ability of students to write news texts after using the group discussion method in class VIII of SMP Negeri 7 Pematangsiantar and, ( 3) The effect of the group discussion method on the ability to write news texts by class VIII students of SMP Negeri 7 Pematangsiantar. This type of research includes pre-experimental research with one group pre-test post-tst design research (Sugiyono, 2019:74), the reason the researcher chooses Pre-experimental research is because this study aims to determine the effect of using group discussion methods in learning to write news texts by VIII grade students of SMP Negeri 7 Pematangsiantar. The results of this study are: (1) the results of the initial test ability (pre-test) in the skills of writing news texts for class VIII-6 SMP Negeri 7 students before the group discussion method is applied, the average score is 66.40. While the results of the final text ability (post-test) after the group discussion method was applied, the average value was 73.12. (2) The results of the score on the assessment aspect of writing news texts before applying the group discussion method obtained the highest score in the vocabulary assessment aspect which amounted to 760 with an average of 23.75 while the lowest assessment aspect was found in the organizational assessment aspect, which amounted to 320 with an average 10. After applying the group discussion method whose value increased, the highest assessment aspect of writing news texts was found in the content aspect, which amounted to 720 with an average of 22.5, while the lowest assessment aspect was found in the mechanical aspect, which amounted to 310 with an average of 9.68. (3) The analysis has been carried out and has been tested statistically. That th is greater than tt (6.72&gt;1.78) causes H0 to be rejected and Ha to be accepted. Thus, it can be concluded that there is an effect of group discussion method on news text writing skills by students of class VIII-6 SMP Negeri 7 Pematangsiantar.
Food Recognition Using Extreme Learning Machines

Abstract: New pictures of current classes are always arriving in open-ended continuous learning, and new classes are constantly appearing. Due to the great generalization capacity which was before deep learning networks, transfer learning was utilized to identify the most effective network for feature extraction from food photos. During transfer learning, it leverages online data augmentation to make up for the paucity of datasets from other orientations. Experimental research has demonstrated that the model's capability to categorize food photos from various potential orientations has been greatly improved by online data augmentation. Second, this study effort decreases the dimensions of retrieved features by using the Relief F technique to rank features. The redundant characteristics make the model's computations more difficult. The best epoch is achieved by getting a training accuracy of 98 percent and a validation accuracy of 92 percent.
On the geochemistry of Gialova lagoon, SW Peloponnesus, Greece

The spatial distribution of lithological characteristics, organic carbon and major / trace elements was studied in the surface sediments of the Gialova lagoon, a shallow water lagoon (&lt;1.0 m) which is located at southwestern Peloponnesus (Greece). The sediment samples were collected on the basis of a detailed bathymetric map and the backscatter properties of the lagoon floor acquired using high resolution side scan sonar on board of an Unmanned Surface Vehicle (U.S.V.). Four main geochemical phases were identified based on the elements – grain size – organic carbon associations. Geoaccumulation index (Igeo) was estimated for heavy metal concentrations showed low to moderate contamination for Mo, Pb, Ni, and Cr.
Competence of university teachers in organizing and conducting distance learning at a university

Distance learning is a form of education that is perfectly suitable for the implementation of contemporary models of education in the information society. This fact relates to the tremendously progressive development of information technology and the increasingly more promising prospects for education. The present study aims to analyze the influence of professional self-improvement on the effectiveness of teachers’ work in the distance mode. Based on an empirical study using the survey method, the levels of competencies comprising competence in the organization and conduct of distance learning among teachers in the information-technical and pedagogical sphere are identified. The results obtained testify to the need to improve the pedagogical qualifications of teachers in the direction of improving competence in the field of information computer technologies and their application in education, as well as in the field of Internet technologies and distance learning.
Twitter Analysis On Real Time Data

Abstract: Sentiment analysis is mainly concerned with identifying and classifying opinions or emotions that are expressed within a text. These days, sharing opinions and expressing emotions through social networking websites has become very common. This paper presents an idea of extracting sentiments out of the tweet and an approach towards classifying a tweet into positive, negative or neutral. This approach can be in many ways useful to any organization, who gets mentioned or tagged in a tweet. Generally the tweets being unstructured in format, first of all the tweet needs to be converted into the structured format. In this paper, tweets are resolved using pre-processing phase and access of tweets has been accomplished via libraries using Twitter API.. We provide additional comparisons and extract alternatives. exams, apprenticeships, etc., are compared to find higher overall performance, and several scoring criteria have been developed for different techniques.
Teknologi Augmented Reality untuk instalasi kelistrikan gedung

The electrical installation stage in the process of building construction have risks to work safety and the operation of the results if the work is not following the General Electrical Installation Requirements (PUIL). This study aims to apply the development of Augmented Reality (AR) technology to provide convenience in the process of working on the electrical installation. Development of AR-based applications by utilizing android-based mobile phone devices which are now commonly owned by the public. The research was conducted by analyzing the electrical installation system in accordance with PUIL standards and its application in an easy-to-understand format, then processing electrical component data as input for 3D objects. Furthermore, the technical data of the building is used to produce AR applications that can be applied to the location of electrical installation work. The application that was built was successfully implemented on an Android-based cellular phone device. The rear camera is used to detect markers as triggers for the emergence of 3D objects in the form of electrical networks and electrical installation components. There are also info features and 3D object animations, as well as video calls as an alternative option for assistance if there are problems during electrical installation work.
Sistem pengendali saklar berbasis Nodemcu ESP8266 dengan aplikasi MQTT dan Google Assistant

The Internet of Things (IoT) provides the ability to connect many things or devices over the internet. Message Queue Telemetry Transport (MQTT) is a Client Server published/subscribed message transport protocol. The protocol runs on top of TCP/IP, or on top of other network protocols that provide sequential, lossless bi-directional connections. The system developed in this study consists of three layers based on the perception layer, network layer and application layer. The perception layer consists of relays that are used to control the screen based on user input. The network layer consists of the MQTT server and Google assistant connected to the IFTTT service. This system was developed with the aim of making it easier for humans to monitor home electrical devices remotely. The test results show that this system can be used to control the switch quickly even though it really depends on the quality of the internet network.
Factors Affecting Digital Literacy in Young Adults

The purpose of this study was to find out the influence of demographic factors, internet use, and smartphone use on young adult digital literacy. This is a quantitative research. The research subjects were young adults aged between 18-24 years using convenience sampling so that 184 people were collected. The research instrument uses a digital literacy scale, The Questionnaire of Experiences Related to the Internet (TQERI) and The Questionnaire of Experiences Related to the Mobile Phone (TQERMP). Data collection was carried out online via Google form for 7 days in July 2022. Based on the results of data analysis, it was found that partially only smartphone use had a significant effect on digital literacy (sig = .069) while internet use did not. But simultaneously, both significantly affect digital literacy (sig= .001). Both can predict 8.2% of digital literacy. The influencing demographic factor is sex, especially women who tend to have higher digital literacy than men (sig=.024, =-1.012). The demographic factor of the area of residence cannot predict the level of digital literacy (sig=.935, =-.182).&#x0D; Keywords: digital literacy, internet, smartphone, demographic
A Deep Neural Network Approach on Spleen Cancer Detection using DenseNet-201

Abstract: Spleen is the largest secondary lymphoid organ and play a crucial role in the regulation of innate and adaptive immune. Among all cancers, spleen cancer is one of the serious diseases which effects minor population across the globe but is potentially fatal, especially if diagnosed in a later stage of development with a 20% survival rate at 6 months. Given the intricacy of the problem, several computer-aided diagnostic methods have been proposed and developed to increase the survival rate Spleen Cancer is a malignancy of white blood cells involving tumour deposits in the spleen. Most splenic cancer do not start in the spleen, and those that do, are almost always lymphomas. Lymphoma is a type of blood cancer that develops in the lymphatic system. Although there are many systems available with the medical industry, but this research is proposed to improve the performance of existing system by employing deep learning feature of Artificial Intelligence (AI) using Convolution Neural Networks (CNN), where Convolution Neural Networks (CNN) has been implemented using DenseNet-201. This research accomplished the desired parameters with values to achieve 99.60% accuracy and 0.1240 % loss while training and testing the model. The research has been supported with the datasets from Kaggle, IEEE transactions on information technology in biomedicine and IEEE International Symposium on Biomedical Imaging. The data set contains three clinical types spleen cancer, such as CLL (chronic lymphocytic leukemia); FL (follicular lymphoma); MCL (mantle cell lymphoma).