Reviewerly/exHarmony huggingface dataset:
Automatic Breast Cancer Lesion Detection and Classification in Mammograms Using Faster R-CNN Deep Learning Network

This paper studies various existing Computer Aided Diagnostics System (CAD) for Mammography and proposes a CAD system for breast cancer lesion with an advanced object detection architecture and validates with an experimental dataset. Mammography is an important tool in the early detection of breast cancers which makes the patient to realize the changes much earlier than they are able to feel the changes in their breasts. CAD system uses digital mammography images and searches for abnormality present in breast such as well-defined or circumscribed mass, calcification, architectural distortion and asymmetry.&nbsp; Feature extraction by Machine learning methods require domain knowledge which is challenging and time-consuming process. Whereas deep learning methods adaptively extract the features by learning from the expert annotated input data.&nbsp; Deep learning methods like convolutional neural networks (CNN) have been a tremendous success in various imaging tasks like image detection, recognition and classification. This paper proposes a CAD system for automatic detection and classification of breast cancer lesion in mammograms based on Faster R-CNN, an advanced, successful object detection framework having region proposal generation and classifier layers.&nbsp; The system generated a mAP (mean Average Precision) value of 0.857 for the testing set, which is the combined performance accuracy of both classification and object detection. Aims: Automatic detection and classification of Breast Cancer lesion in mammograms using Faster R-CNN deep learning network. Methods and Materials: This paper proposes a CAD system for detection and classification of breast cancer lesion in mammograms based on Faster R-CNN, an advanced, successful object detection framework having region proposal generation and classifier layers. The proposed CAD system uses mini-MIAS database (mini-Mammographic Image Analysis Society) with 115 images to train the model. The original MIAS database has 330 digitised mammographic images at 50 micron resolution, which has been reduced to 200 micron resolution with Portable Gray Map (PGM) format file of 1024 x 1024 pixels.&nbsp; Conclusions: This paper considered mini-MIAS database as the database which requires minimal data pre-processing steps with a limited hardware.&nbsp; The enhancement to this CAD system is planning to use CBIS-DDSM database, which is a part of the original DDSM (Digital Database for Screening Mammography) database with annotations by a trained mammographer. The CBIS-DDSM database includes the mammographic images which have been decompressed and converted into DICOM format.
Adaptive pixelwise inference multi-view stereo

Multi-View Stereo (MVS) is a technology that reconstructs the three-dimensional structure of objects or scenes through 2D images and camera parameters. PatchMatch based MVS methods are widely used nowadays. However, these algorithms have two weaknesses: cross-correlation based similarity measurement methods becoming ineffective on regions that are texture-less (e.g. white wall) or have stochastic textures (e.g. grass), as the similarity measurement method such as NCC could not perform well on these regions; Sometimes, the reconstructed result may be stuck into global optimal which heavily drifts from the ground truth because of noise, occlusion and etc. To tackle these issues, we present an MVS pipeline called Adaptive Pixelwise Inference Multi-View Stereo (API-MVS). First, a strategy is proposed to adaptively infer the matching window sizes of each pixel, making the reconstructed results on texture-less or stochastic texture regions have a better trade-off between accuracy and completeness. Second, a new cost function is proposed to integrate the matching cost values computed using different neighboring images, and experiments confirmed that the cost function we used can make locally optimized results closer to the ground truth. We have tested our algorithm on ETH3D benchmarks. The result shows the effectiveness of our method, and it is comparable to state-of-the-art methods.
A Multivariate Fuzzy Clustering-Based Data Imputation for Adaptive Misbehavior Detection in Cooperative Intelligent Transportation Systems

This work proposes a local-global fuzzy-clustering feature extraction scheme for detecting False Data Injection Attacks (FDIA). In this scheme, the data undergo several pre-processing steps including missing values imputation based on the local and global fuzzy-clustering correlation approach. There are four main components of the proposed method: i) data acquisition, ii) standardization, iii) normalization, and iv) imputation. To evaluate the performance of this scheme, the NGSIM dataset (described below) was used. This dataset contains data acquired from the environment using a set of sensors that collect data from the neighboring vehicles. The results show that the accuracy of models trained using said features extracted by the proposed scheme was higher than those proposed by the related studies. This indicates that the local-global fuzzy clustering data imputation approach proposed by this study can estimate the missing values better than existing techniques based on an exhaustive literature review.
Analysis on the change of runoff curve number influence to surface flow debit using ALOS AVNIR-2 data imagery

One part of the hydrologic cycle which has a major influence in increasing the amount of river flow discharge is surface runoff. The higher surface runoff discharge, causing the possibility of surface flooding, therefore required an empirical model that can calculate the amount of surface runoff so as to produce updated data and quickly change according to their needs. One of the empirical methods that can be used to calculate the amount of surface runoff is by using the curve number method. This research is done by utilizing remote sensing image, that is, ALOS AVNIR-2. Data extraction from ALOS imagery includes land cover information using multispectral classification analysis, slope inclination information through visual interpretation, and land use interpretation. The runoff that occurred in Banjarnegara Regency tends to be high, that is, 61.24 percent of the total area of the research area. Large runoff with very high/extreme class spread on the form of hilly land to the old volcano complex at the study site. The runoff in the medium to low class only covers 3.56 percent of the total area and is distributed on the fluvial form with the flat-to-flat slopes. The result of analysis of runoff data is obtained from slope analysis and type of land use in the research location. Increasingly steep slope with little vegetation-land use, then the greater the runoff that occurs. Finally, the research result could be implemented into higher student class activity, especially in remote sensing classes, GIS, cloud computing, and big data analysis. By this process, the students will be improved their skills in analyzing imagery data as well as create new information derived from the remote sensing data.
English Teachers‘ Online Reading Tasks Development Process

The purpose of this research was to observe two processes: 1) developing online reading tasks; and 2) integrating those tasks into online learning platforms. This research employs a descriptive qualitative design. The subject of this study was English teacher at SMAS Laboratorium Undiksha Singaraja. The data was gathered through observation and an interview guide. The data collection procedure began with an online observation and an interview. The data were analyzed according to Miles and Huberman's (2002) framework of analysis, which includes data collection, data reduction, data visualization, and conclusion drawing. The study's findings indicated that 1) activities were used to develop reading tasks using online learning platforms; 2) teacher used five platforms to develop online reading tasks, including WhatsApp, Google Classroom, Youtube, Kahoot, and Quizizz; and 3) the use of online platforms to develop tasks motivates students to learn, increases students' interest in learning, and assists students in learning technology. The implication of this research is that utilizing online platforms to develop tasks benefits students' ability to learn technology
Pengaruh Penggunaan Video Pembelajaran Terhadap Hasil Belajar Komputer 1 Mahasiswa Pendidikan Matematika Semester II TP. 2019/2020 Universitas Pasir Pengaraian

The computer 1 learning outcomes of the second-semester students of the Mathematics Education study program are low because the instruments used have not used instructional videos. A solution is needed in the form of the use of instructional videos. This study wanted to see whether or not there was an effect of instructional videos on the learning outcomes of computer 1. The quasi-experimental method used in this study was that the class A was the experimental class and class B was the control class. The sampling technique used is the saturated sampling technique, where all populations are used as research samples. The average similarity test was used in analyzing quantitative data, while the qualitative data were analyzed descriptively. The average similarity test results utilizing the t-test show where the value of tcount &gt; ttable that 2,56 &gt; 2,015, so it can be concluded that there is an effect of the use of instructional videos on computer 1 learning outcomes second-semester students of the mathematics education study program 2019/2020.
Relay Translation On Dayak Ngaju, Indonesian, And English: Analysis On Cultural Terms In Dayak Mythology “Tatum”

The research described the relay translation of Dayak oral tradition from Dayak Ngaju to Indonesian and from Indonesian to English.The research used a descriptive qualitative method with content analysis and FGD for data collection and interviews for data validation.It attempted to explain the translation techniques in translating specific terms from Dayak Ngaju (L1) to Indonesian (L2) and English (L3).The data were 22 cultural terms in L1-L2 translation.The translation techniques applied were pure borrowing, established equivalent, generalization, description, pure borrowing + addition, established equivalent + pure borrowing, and discursive creation + established equivalent + description.Then, the data in L2-L3 translation were 12 cultural terms.The translation techniques applied were pure borrowing, established equivalent, generalization + pure borrowing, pure borrowing + addition, and established equivalent + pure borrowing + established equivalent.The translator preferred to maintain the originality of cultural terms in L2-L3 translation.
Enhancing Performance of Mwasalat Misr Company in Greater Cairo-Egypt during COVID-19 Pandemic

This research study explores human resource management decisions, management roles, and how they can have a significant and unique impact on the performance of the Mwasalat Misr organization. The survey adopted a qualitative survey design using a sequential narrative approach using unstructured interviews and a stakeholder analysis approach using open-question questionnaires. The research focuses on how to advance the public transport industry by advancing the relationship between HRM and &amp;nbsp;&amp;nbsp;organizational performance. Some of the key unresolved issues that require further research and help industry management investigate these issues and build a more cumulative body of knowledge that has important implications for theory and practice. Suggestions. The study concludes that four factors influence performance: personnel decisions, management roles, employee satisfaction, and cultural and organizational behavior. The COVID 19 pandemic has been found to serve as a parameter between the completed variable and the company&amp;#39;s performance.
The EFL students’ online reading determinants: Perceiving from their selected folklore readings

In an attempt to increase reading performance at university level. This study aims at perceiving the experiential determinants of EFL students’ online reading performance. Data were collected from 182 undergraduate students’ self-rated questionnaire based on the assigned Indonesian folklores in English version through the online reading platforms. Data analysis used descriptive statistics and factor analysis. The results showed that EFL students’ reading habits and reading frequencies and trends were very supportive, whilst reading effectiveness and reading for pleasure supported their reading performance. Tests of chi-square’s four variables were statistically significant indicating the proportional majority of online reading activity. Meanwhile, the Principal Components Analysis (PCA) indicated two components and variables under the eigenvalues’ square root. The interpretation of two components was coherent with the pilot results on the online reading readability scale, analyzed the use of positive and negative affect items as undertaken from the pattern and structure matrix for PCA with the Obliging rotation. EFL students’ online reading is engaging accordingly since students accomplished their reading performance based on individual accessibilities and habits to understand the contents of genres. This study concludes that EFL students’ online reading performance has been practically facilitated by the technology devices multiply. Hence, four online reading variables increased EFL students’ reading awareness and performance accordingly.
Corpus-Based Speech Act Analysis on the Use of Word ‘Lu’ in Cyber Bullying Speech

The purpose of this study was to determine the discursive representation of the word "lu" (you) in written speech on social media that has the potential to express cyber bullying.This research applied the methodology synergy of linguistic corpus and illocutionary speech act analysis.The data in this study included two corpus of cyber bullying taken from stories on several student community accounts on Twitter, Instagram, and Facebook in different periods (2012 and 2020).Analysis on words list and collocation was used to see patterns of using the word "lu" in expressing cyber bullying.Furthermore, concordance was used to deepen the analysis of speech acts and to see the data qualitatively.Based on the results of the corpus analysis, 48 patterns of use of the word "lu" were found.Based on the data analysis from the perspective of speech acts, there were five types of speech acts that appear and were dominated by assertive speech in the form of statements containing taunts and negative nicknames.
Information Retrieval Using Matrix Methods

This research is part of data mining, a sub-section of information retrieval and text mining.This research focuses on finding an approach to getting relevant documents online news documents with a specific threshold value and improving computing performance to get relevant documents with large documents.In this case, the author use news from 3 news sites that are pretty popular in Indonesia, which are included in the top 10 Alexa Traffic Rank (ATR) 2021, namely tribunnews.com,detik.com,and liputan6.com.In searching for relevant news documents, the author determines the threshold value first by calculating the average similarity value of the documents used as the experimental sample.The resulting threshold value is a determinant of the similarity value of each document to be used.The author uses several techniques to assist the research process, such as text mining with the tala method and news document representation techniques using matrix methods, and finally utilizing the cosine size method to determine the similarity of documents with matrix-based search data.The results obtained indicate that the approach using the matrix method and the matrix compression process shows good computational results, so it will be useful for implementation on a large number of documents.
Self-Made Vocabulary Cards and Differentiated Assessments to Improve an Autistic Learner’s English Vocabulary Mastery

As autistic learners exhibit different behaviours from their peers, they need differentiated instruction in learning. Hence, to provide equal learning opportunities for a learner with autism based mainly on the principle of modification changing the expected standard performance of the autistic learner, this study employed differentiated instruction consisting of two treatments in Vocabulary Building class. They were the use of self-made vocabulary cards as the basic learning materials and differentiated assessments consisting of quizzes, mid-semester assessment, and final assessment providing opportunities for recycle and repetition beneficial for vocabulary retention and learning in general. The findings indicated that the autistic learner showed satisfactory results on his mastery of bilingual (Indonesian to English) word equivalence written in the vocabulary cards and thus obtained satisfactory scores in the corresponding assessments. He, however, still struggled in using the words he studied in grammatical and comprehensible English sentences. With teacher’s verbal step-by-step prompts, however, he could formulate simple grammatical sentences. Based on the results, implications, limitations and suggested directions of future studies are presented.
On the interpretation of proper temporal adverbs in Italian

In this paper, we will provide a N-to-D analysis able to account for the punctual vs. habitual reading of proper temporal names in Italian, focusing on names of days, which clearly signal a difference in their possible aspectual encoding at the morphosyntactic level. When these items appear as adverbials modifying an event: i) such event is interpreted as a habitual one if the temporal name is preceded by a definite determiner or an adpositional item; ii) it is interpreted as a punctual one if the temporal name is ‘bare’.
STUDENTS PROBLEMS OF READING SKILL IN NARRATIVE TEXT AT TENTH GRADE OF SMA KARTIKA PEMATANGSIANTAR

Reading is one of the four language skills taught in the process of learning English, along with listening, speaking, and writing. Reading is the ability to comprehend the content of a text. Reading can provide readers with all of the messages and information they require. The purpose of this study is to learn about the students’ reading problems at SMA Kartika 1-4 Pematangsiantar as well as to find a solution to the problems. Descriptive qualitative research was performed in this study. The participants in the study were tenth-grade of MIPA 3 students from SMA Kartika Pematangsiantar, who were found to have reading difficulties. The result of this research found that the students’ problem in reading as follow : internal problems (lack of student vocabulary, a lack of student interest in English subjects, boredom and laziness, and a lack of time to study any English text in class.) And external problems (such as the teacher’s method of instruction, students’ lack of personal dictionaries, the narrative text’s level of difficulty and the lack of textbooks). As a solution, the teacher must play an important role in overcoming the problems faced by students by making teaching techniques more interesting and interactive.
WhatsApp and English Learning: Students’ Perceptions and Challenges in Pandemic Era

Since the pandemic era due to Covid-19, WhatsApp has become an application that is widely used for online learning. In the new normal era, WhatsApp was still the application most widely used by lecturers and students because sending teaching materials was easy and fast. This study investigated students’ perceptions and challenges of utilizing WhatsApp in English language learning amid the pandemic era. The method used was a qualitative method. The researcher used a purposive sampling technique in selecting the participants. The participants in this study amounted to 12 EFL students of 2nd semester of STAIN Teungku Dirundeng Meulaboh. A semi-structured interview was used as data collection techniques. The interview data were analyzed using the Miles and Huberman flow model. The results showed that students used social media to learn and improve their English skills. WhatsApp is the most used application, considered fun, comfortable, helpful, and easy to use. WhatsApp is not only effective and time-saving, it also motivates students in learning English. In addition, WhatsApp uses less internet quota than other online applications. Even so, the internet connection, internet quota, and storage capacity on their devices are still challenges for the students. It can be concluded that the students have positive perceptions of using WhatsApp to learn English.
Kotlin from the perspective of a static analyzer developer

The paper describes a static analysis for finding defects and computing metrics for programs written in the Kotlin language. The analysis is implemented in the Svace static analyzer developed at ISP RAS. The paper focuses on the problems we met during implementation, the approaches we used to solve them, and the experimental results for the tool we have built. The analyzer supports not only Kotlin analysis, but is also capable of analyzing mixed projects that use both Java and Kotlin languages. We hope that the paper might be useful to static analysis developers and language designers.
Cervical Cancer Machine Learning Techniques for Detection Risk Factors and Prevention Measures

Cervical Cancer is considered the fourth most common female malignancy worldwide and represents a major global health challenge. As a result, in recent years, various proposals and researches have been conducted. This study aims to analyze the data presented in current researches regarding cervical cancer and contribute to future research, all through the framework of literature review, based on 3 research questions: Q1: What are the risk factors that cause cervical cancer? Q2: What preventive measures are currently established for cervical cancer? and, Q3: What are the techniques to detect cervical cancer? Findings show that detection techniques are complementary since they are categorized under machine learning. Therefore, we recommend that further study be promoted in these techniques as they are helpful in the detection process. In addition, risk factors can be considered for a greater scope in detection, such as HPV infection, since it is the most relevant factor for the development of cervical cancer. Finally, we suggest to conduct further research on preventive measures for cervical cancer.
Evaluating Novel Speech Transcription Architectures on the Spanish RTVE2020 Database

This work presents three novel speech recognition architectures evaluated on the Spanish RTVE2020 dataset, employed as the main evaluation set in the Albayzín S2T Transcription Challenge 2020. The main objective was to improve the performance of the systems previously submitted by the authors to the challenge, in which the primary system scored the second position. The novel systems are based on both DNN-HMM and E2E acoustic models, for which fully- and self-supervised learning methods were included. As a result, the new speech recognition engines clearly outperformed the performance of the initial systems from the previous best WER of 19.27 to the new best of 17.60 achieved by the DNN-HMM based system. This work therefore describes an interesting benchmark of the latest acoustic models over a highly challenging dataset, and identifies the most optimal ones depending on the expected quality, the available resources and the required latency.