Reviewerly/exHarmony huggingface dataset:
Detector of 3-D salient points based on the dual-tree complex wavelet transform for the positioning of hippocampi meshes in magnetic resonance images

Brain Magnetic Resonance (MR) image segmentation methods based on deformable models depend on the initial positioning to maximize the chances of successful segmentation. To minimize this limitation, salient-point based registration is used to perform the initial positioning of brain structure meshes close to their image target representation. The analysis of brain structures (such as the hippocampus) can help in the diagnosis and follow-up of neurodegenerative diseases like Alzheimer's. We present a technique for detection and description of 3-D salient points, which combines filter response maps estimated for different scales and orientations of the dual-tree complex wavelet transform (DT-CWT). We apply our technique to detect salient points in volumetric brain MR images and use the detected points in a positioning methodology. To illustrate the applicability, we applied our method for the positioning of hippocampi meshes in 3-D brain MR images and assessed the results by overlapping the positioned meshes with manual annotations made by medical specialists. Our method yielded mean values of normalized Dice Similarity Coefficient (nDSC) of 0.74/0.68 and Hausdorff Average Distance (HAD) of 0.73/0.75 for the left and right hippocampus, respectively. The mean nDSC and HAD results of our detector were significantly better than the ones achieved by an Affine and a Phase Congruency (PC) guided positioning. The detection via DT-CWT decomposition is computationally less demanding than the detection via PC and represents a robust alternative for the positioning of mesh models.
Commissive Speech Act in Indonesian Presidential Debate

A presidential debate is one of the campaign media which has a function to promote a presidential candidate to be a president. A linguistics theory of meaning was used to describe the utterances of the illocutionary act. This study was aimed to find a commissive speech act and its function in the first Indonesian presidential debate in 2019. The data source of this study was a video taken from Kompas TV channel on YouTube. The data of this study were utterances produced by the candidates. The data were collected by watching and note-taking techniques. As a result, 20 utterances belonged to the commissive speech act produced by Jokowi, Prabowo, and Sandi. However, there were no commissive speech act utterances produced by Ma'ruf. The conclusion is that the candidates mostly used promise act in producing utterances. The promise acts appear in the future tense, if clause condition sentence, and expression of InsyaAllah. Meanwhile, the function of producing utterances in this study is to show the candidates' capability to gain the consideration of society to vote one of them with a good sympathy.
How we tried to JATS XML

This is a story about how an Open Journal Systems-based library publishing service tried (and failed) to implement XML in one of its publications. We ran a small project to look at how journals we support could develop a JATS XML-based publishing workflow using existing open software tools.
Learning Constraints for Structured Prediction Using Rectifier Networks

Various natural language processing tasks are structured prediction problems where outputs are constructed with multiple interdependent decisions. Past work has shown that domain knowledge, framed as constraints over the output space, can help improve predictive accuracy. However, designing good constraints often relies on domain expertise. In this paper, we study the problem of learning such constraints. We frame the problem as that of training a two-layer rectifier network to identify valid structures or substructures, and show a construction for converting a trained network into a system of linear constraints over the inference variables. Our experiments on several NLP tasks show that the learned constraints can improve the prediction accuracy, especially when the number of training examples is small.
STUDENTS’ APPREHENSION IN CLASS PARTICIPATION AND FAMILY COMMUNICATION

Being an active student in school motivates a student to be more confident in performing their activities. Somehow, not all the students are confident to show their capabilities in performing in class because they feel apprehended due to some factors such as their communication in their families. This study determines the correlation between the family communication at home and the apprehension in the class participation of the Senior High School students in a certain school of Mandaue City. This study uses descriptive design with checklist scaling questionnaire as being used for gathering data. After the data were being gathered, the data were then analyzed using of weighted mean to determine the level of family communication and the students’ apprehension; chi-square to determine the association between family communication and their apprehensions. Family communication is experienced often. The students’ family members are satisfied of the communication in the family. The students’ family members sometimes can express their feelings and ideas among themselves. While the level of students’ apprehension in their class participation is experienced sometimes, students feel comfortable of communicating in class. In addition, students who dislike participating in group discussions seldom experienced apprehension. Finally, students’ apprehension is significantly associated to family communication.
Sentiment Analysis of E-Commerc Brand Review Using Multinomial Text Naïve Bayes

Technological developments has impact on buying and selling transactions online or e-commerce. Bukalapak is the most popular e-commerce content which used for buying and selling and has a mobile phone and website application, which gives users access to provide sentiment analysis reviews can be used to monitor consumer reviews of their products. Naive Bayes classifier is the one of classification method. Naive Bayes classifier can be divided into two, namely multivariate Bernouli and Naive Bayes multinomial text. Multinomial text Naive Bayes able to reduce errors in document classification. The results obtained by the review given by Bukalapak users on Google Play using the Multinomial Naive Bayes show that 89% of the reviews rated positively with the prediction accuracy of Naive Bayes by 91.95%. As much as 80.71% of reviews give a rating of 5. However, there are some negative reviews that are mostly written, namely  “Lambat“, “Ribet“, “Mengecewakan“, “Susah“, and “Perbaiki” it can be used to reference material for Bukalapak in improving the services. Keywords: E-commerce, Multinomial Naive Bayes,  Text Mining,  Sentiment Analysis
Media Pembelajaran Pengenalan Metamorfosis Sempurna Dan Tidak Sempurna Menggunakan Augmented Reality

Utilization of Augmented Reality (AR) technology as a learning medium about perfect and imperfect metamorphosis aims as a tool in the alternative learning and teaching process between teachers and students by visualizing 3D objects in realtime. This multimedia application for introducing perfect and imperfect metamorphosis is based on Augmented Reality by referring to the material in the Science books for Elementary School grade IV (Four) curriculum 2013. The methodology used in developing this application is the Luther Sutopo development method. Where this method consists of 6 (Six) stages, namely concept, design, material collecting, assembly, testing, and distribution. The results or the output of the application that the author built is an android application using Augmented Reality technology to show the shape or form of the stages of animals that experience perfect metamorphosis and imperfect metamorphosis. The conclusion of this study is that the overall response of the end user to this application is quite good. Where in some questions related to this AR application has given good answers. This is evidenced by some of the tests that the authors have conducted on applications where the testers are writers and end users.
Multi-pose facial expression recognition using rectangular HOG feature extractor and label-consistent KSVD classifier

In this paper, a new approach to the classification of facial expressions from multiple pose images is proposed. In this approach, a rectangular histogram of oriented gradient (R-HOG) algorithm is first designed to extract features of face images. The parameters of the R-HOG algorithm, which is a modification of the original HOG algorithm include cell shape, cell size, block size, and the number of orientation bins. The R-HOG is capable of capturing more discriminative texture features of different facial expressions. In addition, a supervised dictionary learning classifier, the label-consistent K-SVD (LC-KSVD) algorithm, is adopted to recognise the facial expression of the subject. To investigate its effectiveness, the proposed technique was applied to classify emotional states of the face images in the two public available facial expression datasets: KDFE and RafD. The experiment study showed that the new method outperformed in many aspects those methods reported in the literature tested with the same datasets. First, the new method handles pose variations better. Second, it is more robust in cases where the size of a training dataset is small. Finally, it's accuracy performance is more consistent measured by standard deviations.
First steps towards the Lithuanian word association database

This paper introduces the first version of the Lithuanian database of free association norms. This is an attempt to provide an open-access resource, which would be helpful for psycholinguists, linguists, computational linguists, and students. This version of the database includes 277 cue word forms. The responses were collected from 304 participants. In total 15,612 association pairs were recorded. The paper presents the procedure of collecting free associations and additional data available for researchers. It also provides a list of all cue words with their five most frequent associates and some summary statistics.
Meningkatkan Keaktifan Siswa Kelas 4 dalam Proses Pembelajaran di MI Yanida

In this study, he will examine student learning outcomes using the demonstration method in his learning on Pkn subjects. This study aims to find out how to use the demonstration method, using the demonstration method for learning outcomes of 4th grade students at MI Yanida. Data collection methods in this study use the method namely: Method of observation, interviews. The results of this study will test student learning outcomes taught by using the demonstration method in MI subjects at Yanida MI, the use of demonstration methods by teachers in grade 4 students for Pkn subjects in accordance with the guidelines for implementing good demonstration methods so that good learning results are obtained . from the use of demonstration methods conducted by the teacher. the use of demonstration methods in describing student learning outcomes by using the demonstration method in pkn for grade 4 students shows good results.
Research on Application of Improved S Transform in High Frequency GNSS Data Processing Results During Earthquake

The high-frequency GNSS data at the time of earthquake was obtained by dynamic single-epoch positioning solution, and the GNSS displacement results were obtained. However, the seismic-time GNSS displacement result after dynamic single-epoch solution contains a lot of noise. It has a great impact on the analysis and research of the displacement during the earthquake, in order to minimize the noise impact in the results and improve the accuracy of dynamic positioning. Traditionally, the S transform denoising method is used to denoise the processing results, but the denoising effect is affected because its time resolution is limited. This paper improves the S-transform method and improves its time-frequency resolution. The principle of S-transform and improved S-transform is introduced. The improved S-transform is used to denoise the high-frequency GNSS single-epoch dynamic positioning results after earthquake processing by GAMIT/TRACK, which greatly removes the noise of displacement results and improves The analysis and research of the dynamic positioning accuracy and the high-frequency GNSS displacement results during the earthquake are made to more accurately determine the time when the GNSS seismic wave arrives at the observation station. Finally, based on the characteristics of high-frequency GNSS acquisition of seismic instantaneous deformation information, this paper proposes an improved S-transform method combined with a trend term denoising method, which can minimize the effect of positioning errors of long-period low-frequency displacement signals, which is more conducive to the in-depth study of GNSS Seismology.
Testing the Determinants on the Onset of Elementary School Students’ Stress using the Multi-level Survival Analysis

최근 초등학생이 직면하는 스트레스의 수준이 점점 높아지고 이로 인해 여러 가지 개인적&#8228;사회적문제를 야기함에도 불구하고 이들의 스트레스가 어느 시점에서 최초로 발생하는지, 각 요인이 스트레스 발생에 어느 정도의 영향을 미치는지에 대해 명쾌하게 밝혀지지 않고 있다. 이에 본 연구는 초등학생의 종단적인 스트레스 양상과 요인을 분석하기 위해 경기도교육연구원에서 제공한 경기교육종단연구(GEPS)의 1-3차년도 자료를 활용하였고, 초등학교 4학년 3,541명을 기점으로 다층생존분석을 실시하였다. 연구 결과는 다음과 같다. 첫째, 학년이 올라갈수록 초기 스트레스 발생 비율이 증가하였다. 둘째, 초등학생이 느끼는 스트레스 유형 중 가장 높은 비율을 차지하는 스트레스 유형은 가정스트레스이다. 셋째, 정신건강과 부모의 양육태도는 모든 스트레스의 주된 원인이다. 넷째, 초등학생들이 느끼는 스트레스는 대인관계와 밀접한 상관이 있다. 다섯째, 학교스트레스와 사회스트레스는 교육의 영향을 많이 받는다. 이상의 연구 결과를 바탕으로 시사점과 후속연구의 가능성을 제시하였다.Recently, the level of stress faced by elementary school students has been increasing, causing many personal and social problems. Nevertheless, it is not clear at what point their stress first occurs and how much each factor affects. Therefore, this study used data from the Gyeonggi Provincial Institute of Education (GEPS) to analyze the longitudinal stress patterns and factors of elementary school students, and conducted a multi-level survival analysis based on 3,541 fourth graders. The results are as follows: First, the rate of early stress increases as the grade goes up. Second, the most frequently occurring stress among elementary school students is family stress. Third, in all of the noted stress, depression, anxiety, and parental situation had a major influence. Fourth, the stress of elementary school students is closely related to interpersonal relationships. Fifth, civil education provided at school level had an influence in discouraging stress. Based on these results, practical strategies were proposed and the possibility of follow-up study was presented.
An Objective Test Using Optical Answer Sheets :

Focusing on digitalization of answering and automation of grading of tests, this paper describes migration from descriptive test to an objective test format using optical answer sheets. In a specific example, a test was used to generate a class diagram from source code. In doing so, it proposes an answer format that would not impede freedom of answering. It describes the process of trial and error through the development of its proposal as well as the adoption of optical answer sheets and the questions used. It then reports on practice using these answer sheets. In the practical example it presents, grading was completed in approximately 20 minutes from the time the answer sheets were scanned after the test.
GSU Library Research Guides: Web Savvy -- General Guide: What You Can Find

A multi-page tutorial on evaluating web sites, for beginners and those who think they know. What you can find on the open web.
Cyberthreats in 2025

Presents a virtual roundtable discussion of the future for cyberthreats and cybersecurity through 2025. The topic of discussion is what the upcoming cyberthreats in 2025 might be. We could have asked about other years, such as 2030 or 2035. However, for this topic, the larger the number, the more the answers become sheer speculation. We believe that distant, futuristic speculation is of little value to the reader, given the relentless hacks that occur daily. In this VRT, we invited six experts to respond to 12 questions. Their written responses may have undergone minor edits. However, as organizers, we attempted to keep their words as verbatim as possible.
Features Dependent on the learners’ discourse competence: Development of a rating scale description in a speaking test - Focusing on the REFUSAL task -

The purpose of this study is to develop an empirically verified grading scale description using the ‘performance data-driven approach’ suggested by Fulcher(1987). This study focuses on creating a standardized category of the discourse features for Korean language learners depending on their discourse competence. The data used in the study were collected from 50 Korean language learners by conducting a CBT speaking test using the ‘REFUSAL’ task. The speech data were graded by five raters, and the speech samples were categorized into five different groups according to their grading results. Additionally, the speech data were transcribed and analyzed using discourse analysis. According to the analysis, five groups of different discourse competence level demonstrated distinct discourse features. The group with the highest level of discourse competence showed a complete four or three level discourse structure and a coherent discourse equivalent to the native Korean speakers. Furthermore, the group with a higher level discourse competence expressed its willingness to help and apologized more. Meanwhile, the groups with a lower level discourse competence displayed incomplete discourse structures and numerous negative factors such as repetitions and direct refusal expressions. The results of this study can be utilized not only as objective data for developing a speaking scale description for the Korean language speaking test, but also for the development of effective teaching discourse method, rater training courses and instrumental textbooks.
Careful analysis of XRD patterns with Attention

The important peaks related to the physical properties of a lithium ion rechargeable battery were extracted from the measured X ray diffraction spectrum by a convolutional neural network based on the Attention mechanism. Among the deep features, the lattice constant of the cathodic active material was selected as a cell voltage predictor, and the crystallographic behavior of the active anodic and cathodic materials revealed the rate property during the charge discharge states. The machine learning automatically selected the significant peaks from the experimental spectrum. Applying the Attention mechanism with appropriate objective variables in multi task trained models, one can selectively visualize the correlations between interesting physical properties. As the deep features are automatically defined, this approach can adapt to the conditions of various physical experiments.
PRESS: A personalised approach for mining top-k groups of objects with subspace similarity

Personalised analytics is a powerful technology that can be used to improve the career, lifestyle, and health of individuals by providing them with an in-depth analysis of their characteristics as compared to other people. Existing research has often focused on mining general patterns or clusters, but without the facility for customisation to an individual’s needs. It is challenging to adapt such approaches to the personalised case, due to the high computational overhead they require for discovering patterns that are good across an entire dataset, rather than with respect to an individual. In this paper, we tackle the challenge of personalised pattern mining and propose a query-driven approach to mine objects with subspace similarity. Given a query object in a categorical dataset, our proposed algorithm, PRESS (Personalised Subspace Similarity), determines the top-k groups of objects, where each group has high similarity to the query for some particular subspace. We evaluate the efficiency and effectiveness of our approach on both synthetic and real datasets.
Tuning a variational autoencoder for data accountability problem in the Mars Science Laboratory ground data system

The Mars Curiosity rover is frequently sending back engineering and science data that goes through a pipeline of systems before reaching its final destination at the mission operations center making it prone to volume loss and data corruption. A ground data system analysis (GDSA) team is charged with the monitoring of this flow of information and the detection of anomalies in that data in order to request a re-transmission when necessary. This work presents $Δ$-MADS, a derivative-free optimization method applied for tuning the architecture and hyperparameters of a variational autoencoder trained to detect the data with missing patches in order to assist the GDSA team in their mission.
An assessment of e-book collection development practices among Romance language librarians

Purpose The purpose of this paper is to describe the collection development practices regarding e-books among librarians who manage French, Italian, Portuguese and Spanish (Romance) materials. The authors aim to describe factors that influence acquisition of e-books for Romance language collections to confirm librarians’ perception that humanities researchers prefer print and library administrators’ attitudes toward e-books. Design/methodology/approach This study collected data using a mixed-method approach of a survey and focus groups. Findings This study confirms that user preference is the primary consideration of Romance librarians in selecting e-books. Contrary to librarians’ perceptions, this study found that humanities faculty and students are not averse to using e-books for specific purposes such as searching, targeted reading and course materials. While restrictions on lending e-books are a concern, Romance librarians are focused primarily on serving the needs of their core constituencies. Research limitations/implications The practice of adding call numbers to individual e-books varies among institutions. Individual e-book titles in large packages do not necessarily get added to the catalog, thus making it very difficult to compare e-book collections between institutions. Originality/value This study endeavors to unify the anecdotal narratives and factors that influence the acquisition of e-books by Romance librarians.
Class Fields of Complex Multiplication: translation of "Die Klassenkörper der komplexen Multiplikation" by Max Deuring

This is an English translation of the monograph "Die Klassenkörper der komplexen Multiplikation" by Max Deuring, published in 1958 as Enzyklopädie der Mathematischen Wissenschaften, Band I-2, Heft 10, Teil II by B.G. Teuber Verlagsgesellschaft, Stuttgart. It gives a systematic exposition of the analytic method in the theory of complex multiplication -- the interrelations between elliptic functions, modular functions and algebraic numbers. This translation was done as an exercise for learning the German language. The mathematical notation and terminology are kept as closely as possible to those given in the German original work. No attempt has been made to modernize the exposition, other than rectifying a (very) few obviously-correctable typographical errors.