Reviewerly/exHarmony huggingface dataset:
ENHANCING DESCRIPTIVE PARAGRAPH WRITING OF SECONDARY STUDENTS THROUGH SHARED WRITING

The objective of the study is to find out whether or not there was a significant difference in descriptive paragraph writing enhancement of secondary students who were taught through shared writing and those who were not. This study was conducted by using an experimental method. The sample of the study was 35 eighth grade students taken by using convenience sampling technique, 18 students belonged to experimental group and 17 students belonged to control group. The data were collected through pretest and posttest. In order to maintain validity, content validity was applied. Then, two raters were used to maintain reliability of the result. The experimental group was taught for twelve meetings by using Shared Writing. The result showed the students in the experimental getting the mean 14.67 with standard deviation 2.058 and control group getting the mean 12.00 with standard deviation 1.414 got a significant improvement in the posttest. There was a better significant improvement in descriptive paragraph writing in the experimental group who are taught by using Shared Writing if compared to the students in the control group.
A Subjective Expressions Extracting Method for Social Opinion Mining

Opinion mining plays an important role in public opinion monitoring, commodity evaluation, government governance, and other areas. One of the basic tasks of opinion mining is to extract the expression elements, which can be further divided into direct subjective expression and expressive subjective expression. For the task of subjective expression extraction, the methods based on neural network can learn features automatically without exhaustive feature engineering and have been proved to be efficient for opinion mining. Constructing adequate input vector which can encode sufficient information is a challenge of neural network-based approach. To cope with this problem, a novel representation method that combines the different features with word vectors is proposed. Then, we use neural network and conditional random field to train and predict the expressions and carry out comparative experiments on different methods and features combinations. Experimental results show the performance of the proposed model, and the F value outperforms other methods in comparative experimental dataset. Our work can provide hint for further research on opinion expression extraction.
Penerapan Extreme Programming Untuk Merancang Aplikasi Kemahasiswaan Berbasis Android

Student activities reports are one of the standards assessed in submitting accreditation forms for study programs and faculties. Student data for 5 years must be recorded along with supporting evidence to be submitted and assessed by the assessor. This application was created using extreme programming and the React Native framework with input from the student affairs and quality assurance section. The testing process uses ISO 9126 with stakeholders and testing the effectiveness, efficiency, usefulness to ensure that the application can be used and fits the functional needs from the relevant sections. The research results are in the form of an application which contains menu of student data, student activity units, Atmaluhur alumni, activity proposals, student affairs agendas, tracer study results, and student achievements. This application, after being tested for the functional aspects, gets a value of 82.65% (good criteria), the reliability aspect is 84.03 (good criteria), the usability aspect is 87.20 (very good criteria), and the efficiency aspect is 80.40 (good criteria). ), so that the overall average is 83.57 (good criteria).
The Realization of Imperative Politeness of Indonesian Language Teacher in Teaching Learning Process in Krista Citra Parakan Junior High School

The objective of this study is to describe the forms, strategies, functions, and meanings of imperative politeness used by a teacher of Bahasa Indonesia of Krista Citra Parakan Junior High School.This is a descriptive qualitative research.The data were collected by using observation method.Two techniques employed in the observation were involved observation and note taking.The data collected were then analyzed by using extralingual comparing method.The results show that there are several forms of imperative politeness employed by the subject of the research; they are tact maxim, generosity maxim, approbation maxim, modesty maxim, agreement maxim, and sympathy maxim.The strategy used by the teacher in employing the imperative politeness is positive politeness.The functions of employing positive politeness are class management, motivation, academic instruction, and evaluation.The meanings of the employment of imperative politeness are (1) pragmatic imperative as "command" meant to order, to persuade, and to prohibit someone from doing something, (2) pragmatic imperative as "request" meant to request someone to do something, and (3) pragmatic imperative as "advice or recommendation" meant to allow someone to do something.
Rancang Bangun Sistem Informasi Geografis Rekomendasi Cagar Budaya Menggunakan Metode Analytic Hierarchy Process

Salatiga City is a town located in the province of Central Java. In this town, there can be found many cultural heritage buildings that were built in the mid-18th century to 1940. Potential visitors would increase easier if a geographic information system is built. Tourists who visit can access the website to select or search for cultural heritage that they want to visit, therefore the availability of a geographic information system that provides information and data on the location of cultural heritage in digital maps is needed. The system must also consider aspects of the cultural heritage rating, the price of admission, and the condition of the cultural heritage to provide recommendations on which cultural heritage to be visited. Therefore the geographic information system of cultural heritage recommendations uses the analytical hierarchy process (AHP) method which can calculate multi- criteria, multi alternatives, and provides cultural heritage recommendations. This system combines geographic information system as a provider of cultural heritage information and AHP decision support system to assist tourists in choosing cultural heritage.
CLAY COMPOSITE WATER FILTERS: THE CASE OF FLUORIDE, NITRITE AND Escherichia coli REMOVAL

Inorganic ceramic materials is receiving more attention in recent times due to their unique characteristics which include different pore structures, hydrophilic surfaces, high chemical, thermal and mechanical stabilities that offer avenues for application in water treatment.In the present work, cost-effective clay ceramic water filters of different designs were developed from clay (50, 60, and 70) %, sawdust (15, 20, 25, and 35) %, grog (5, 10 and 15)% ratios plus 5% bone char by volume and sintered at temperature of 950ºC for 6 hrs.For the flow rate, fluoride and nitrite tests synthetic waters were used, while for Escherichia coli removal efficiency test of the filter diluted wastewater sample collected by purposive sampling methods from Modjo River was used.The analysis of the optimal performing sintered filter by X-ray diffraction revealed the existence of mixed phases such as quartz, mulite and ilite.The surface functional group analysis by infrared spectroscopy showed the presence of strong bands at 3696 cm -1 , 3622 cm -1 , 3450 cm -1 of hydroxyl linkages.Field emission scanning electron microscopy of fractured filter surfaces with better performance showed the formation of interconnected porous microstructure materials.The ceramic water filter developed from 50% clay, 15% grog, 35% sawdust, and 5% bone char, (C950-50-35-15), characterized with total porosity 36.33±0.05%,displayed flow rate 1.91±0.55L/hand E. coli, nitrite, and fluoride removal efficiencies of 99.91±0.09%,76.00±0.22%,and 96.8±0.41%respectively.
Choosing What to Believe - New Results in Selective Revision

Selective Revision was proposed by Fermé and Hansson as a belief revision operation in which it is possible to accept only a part of the input information. In this paper, we extend Selective Revision to belief bases and also to logics not closed under negation.
AN ADVANCED FACE DETECTION AND RECOGNITION

Image or video Face Identification is a popular subject for research in biometrics. Most public places usually have video capture surveillance cameras and these devices have an important safety benefit. The identification of the face has played a significant role in the monitoring system since the entity does not need assistance. It is widely recognized all over the world. Uniqueness and Validation are the main benefits of facial recognition over other biometrics. Since, Human face is a highly variable and dynamic subject, the detection of the face in computer vision is a difficult problem. Precision and Recognition speed are a big problem in this area. The purpose of this paper is to test various facial detection and recognition approaches, and provide a full solution for facial detection and recognition in an image-based manner with a higher degree of accuracy and an improved response time. This suggests a solution focused on experiments carried out on different facial rich datasets with respect to topics, images, attitudes, ethnicity and color.
HOW DOES SHANNON’S SOURCE CODING THEOREM FARE IN PREDICTION OF IMAGE COMPRESSION RATIO WITH CURRENT ALGORITHMS?

Abstract. Images with large volumes are generated daily with the advent of advanced sensors and platforms (e.g., satellite, unmanned autonomous vehicle) of data acquisition. This incurs issues on the storage, processing, and transmission of images. To address such issues, image compression is essential and can be achieved by lossy and/or lossless approaches. With lossy compression, a high compression ratio can usually be achieved but the original data can never be completely recovered. On the other hand, with lossless compression, the original information is well reserved. Lossless compression is very desirable in many applications such as remote sensing, geological surveying. Shannon's source coding theorem has defined the theoretical limits of compression ratio. However, some researchers have discovered that some compression techniques have achieved a compression ratio that is higher than the theoretical limits. Then, two questions naturally arise, i.e., “When this happens?” and “Why this happens?”. This study is dedicated to giving answers to these two questions. Six algorithms are used to compress 1650 images with different complexities. The experimental results show that the generally acknowledged Shannon’s coding theorem is still good enough for predicting compression ratio by the algorithms with consideration of statistical information only, but not capable of predicting compression ratio by the algorithms with consideration of configurational information of pixels. Overall, this study indicates that new empirical (or theoretical) models for predicting lossless compression ratio can be built with metrics capturing configurational information.
Generating generalized necklaces and new quasi-cyclic codes

In many cases there is a need of exhaustive lists of combinatorial objects of a given type. We consider generation of all inequivalent polynomials from which defining polynomials for constructing quasi-cyclic (QC) codes are to be chosen. Using these defining polynomials we construct 34 new good QC codes over GF(11) and 36 such codes over GF(13). In many cases there is a need of exhaustive lists of combinatorial objects of a given type. We consider generation of all inequivalent polynomials from which defining polynomials for constructing quasi-cyclic (QC) codes are to be chosen. Using these defining polynomials we construct 34 new good QC codes over GF(11) and 36 such codes over GF(13).
STUDENTS’ PERCEPTION ON THE USE OF RUANGGURU APPLICATION IN THEIR ENGLISH LEARNING

Abstract. This study aimed at finding out the Students’ Perception on the Use of Ruangguru Application in Their English Learning. The researcher applied mixed method (quantitative and qualitative). The population of this research was the second grade students of Senior High School of Athirah Islamic School Makassar in 2019/2020 academic year. The sample was taken consisted of 24 students which were taken by using simple random sampling technique. The data were obtained through the questionnaire were analysed and tabulated based on the classification of perception using Likert scale and the data from interview were analysed by recording and transcribing it. The results of data analysis showed that (1) students’ perception was positive on the use of Ruangguru application in their English learning by mean score 70 (2) based on the students’ classification that 5 (20.8%) students classified as Strongly positive, 10 (41.7%) students classified as Positive, 5 (20.8%) students classified as Moderate, 3 (12.5%) students classified as Negative and 1 (4.5%) students classified as Strongly negative. This was indicated that most students like using Ruangguru in their English learning.
THE USE OF THE MULTISENSORY METHOD NUMICON IN LEARNING BASIC MATHEMATICAL SKILLS BY STUDENTS WITH MODERATE MENTAL DISABILITIES

The article “The use of the multisensory method Numicon in learning basic mathematical skills by students with moderate mental disabilities” briefly analyses basic math learning skills of the student with moderate mental disabilities and gather the teaching methods that can be used by teachers. The multisensory method Numicon is described in detail how it can be used in work with the students with moderate mental disabilities. The description of the author’s methodological material “Mathematics with Numicon” is also provided. The results of the research are summarized about the basic mathematical skills for the students with moderate mental disabilities by using the multisensory method and the Numicon materials, and authors methodological material “Mathematics with Numicon”.
Quantum Hierarchical Agglomerative Clustering Based on One Dimension Discrete Quantum Walk with Single-Point Phase Defects

As an important branch of machine learning, clustering analysis is widely used in some fields, e.g., image pattern recognition, social network analysis, information security, and so on. In this paper, we consider the designing of clustering algorithm in quantum scenario, and propose a quantum hierarchical agglomerative clustering algorithm, which is based on one dimension discrete quantum walk with single-point phase defects. In the proposed algorithm, two nonclassical characters of this kind of quantum walk, localization and ballistic effects, are exploited. At first, each data point is viewed as a particle and performed this kind of quantum walk with a parameter, which is determined by its neighbors. After that, the particles are measured in a calculation basis. In terms of the measurement result, every attribute value of the corresponding data point is modified appropriately. In this way, each data point interacts with its neighbors and moves toward a certain center point. At last, this process is repeated several times until similar data points cluster together and form distinct classes. Simulation experiments on the synthetic and real world data demonstrate the effectiveness of the presented algorithm. Compared with some classical algorithms, the proposed algorithm achieves better clustering results. Moreover, combining quantum cluster assignment method, the presented algorithm can speed up the calculating velocity.
“I Did What I Believe Is Right”: A Study of Neutralizations among Anonymous Operation Participants

Our knowledge of online activists or hacktivists is growing, but it is still far from complete.The reasons why some of these individuals violate computer laws or how they justify their behavior remains elusive, yet one particular framework that lends itself to understanding a hacker or hacktivist's belief system is Sykes and Matza's (1957) neutralization theory.The present study involved a content analysis of publicly available commentary found online and made by participants in Anonymous operations against United States targets from 2008-2013.Over 13,000 words were analyzed, and of the 384 passages of text and phrases, roughly 62% of passages contained some type of neutralizing statement, whereas 38% of passages were coded as containing no neutralization technique.Among the 238 passages and phrases of neutralizations, over half contained neutralizations that reflected condemnation of the condemners, appeal to a higher moral principle, and denial of the victim.Another important finding was that several participants in Anonymous operations justified their actions as simple acts of protest or civil disobedience.While this study sheds light on how hacktivists may justify their behavior, it also paves the way for exploring other neutralizing techniques and signals the need for developing crime-specific neutralizations.
Motion Balance Ability Detection Based on Video Analysis in Virtual Reality Environment

In recent years, smart camera devices under the Virtual Reality (VR) environment have been widely popularized. These devices can be equipped with fast and effective computer vision applications, including the detection of the balance ability of moving targets. Moving target balance ability detection plays an important role in public security, traffic monitoring and other fields, and is also a basic technology for many vision applications. Therefore, the requirements for accuracy and completeness of detection are getting higher and higher. This article proposes a tracking method Motion Model and Model Updater (MMMU) based on the balance acquisition and model update and intelligent adjustment of the motion model. Improved Motion Model (IMM) is a background sample balance acquisition algorithm based on simple linear iterative clustering, completes the abstraction of background images. Different from other update strategies with a fixed number of frames, the update strategy based on image histogram contrast relies on the human selective forgetting mechanism to better avoid burst frames and process similar frames. Since the data used to detect the balance ability of moving targets is inherently unbalanced, the idea of dealing with imbalance in data mining is introduced into it, and the problem of balance ability detection of moving targets is studied from the perspectives of downsampling and oversampling. In addition, temporal and spatial oversampling of the foreground and selective downsampling of the background are performed to reduce the imbalance of the data set, and the resampled data set is used for modeling and classification. The feasibility of the MMMU algorithm is tested through experiments, and the motion balance ability of the foreground target is detected relatively completely.
Multilevel thresholding and Morphological Relationship Approach for Automatic Detection of Anterior and Posterior Commissure in Mid-sagittal Brain MRI

Most of neuroimaging applications tend to still rely on expert knowledge in determining anatomies of the brain.For example in Parkinson's disease surgery, detection of the anterior commissure (AC) and posterior commissure (PC) are still done manually by doctors.Previously, various methods have been developed related to the automatic detection of AC and PC.However, the majority of previously methods have several drawbacks, such as only compatible on T1-W or T2-W, only compatible for data with the same matrix size, and requires a time-consuming training process.This study proposes a new strategy by combining a multilevel thresholding and morphological relationships approach for automatic detection of AC and PC.The process divided into 4 main stages: preprocessing, multilevel thresholding, segmentation, and detection of AC and PC.The segmentation is performed on several anatomies of the brain including corpus callosum, fornix, and colliculus.From the experiment, it can be concluded that the use of multilevel thresholding and morphological relationship was successfully detecting AC and PC with the mean error were 1.02 mm and 1.06 mm, respectively.The proposed method can perform an automatic detection of AC and PC with simply algorithm, does not require a large of diverse data sets for the training process, without training process that takes up time, and reliable on the diversity of MRI since it is compatible for T1-W and T2-W with various matrix sizes of 256 x 256 and 512 x 512 pixels which cannot be handled by previous researches.
A Light-Weight Deep CNN Object Detection Framework Based on Dense Connections

For deep neural network (DNN) object detection frameworks, increasing the depth of the convolutional neural network (CNN) layers has been regarded as one of the most efficient methods to improve the detection accuracy. However, with the increasing of the number of neural network layers, the parameters of the network will then increase exponentially and even introduce the gradient disappearance problem. These problems limit the applications of these methods in the scenarios with constrained hardware resources. Hence, in order to reduce the parameters and improve the parameter utilization, a lightweight deep CNN object detection framework (LWOD) is proposed. This framework builds dense connections between different convolutional layers and concatenates the feature maps of multiple channels. It detects the objects by combining multi-layer feature maps of the same scales. Experimental results show that the detection accuracy of the proposed framework can reach 71.2% without pre-training models. The parameters of the whole framework can be reduced by 66.1% compared with the prior object detection framework.
EXPLORING CULTURAL HERITAGE COLLECTIONS IN IMMERSIVE ANALYTICS: CHALLENGES, BENEFITS, AND A CASE STUDY USING VIRTUAL REALITY

Abstract. Immersive analytics, at the intersection of visual analytics and virtual reality has recently gained some traction. Taking a similar approach, VaRt-DataExplorer project is concerned with exploration of data spaces in Virtual Reality (VR) in the context of cultural heritage collections. Our main objective is to facilitate better a understanding and insight into spatially referenced cultural heritage data sets. Within the scope of the project, this goal would be achieved by providing potentially ‘intuitive’ forms of real time interaction with the data, and rendering quickly recognizable visuospatial representations to offer more context to cultural artifacts. In particular, a spatial context is provided to the viewers by referencing geographical aspects of the data. Due to the incomplete and imprecise nature of data in this domain, thoughtful attention is given to visualization fidelity. Our initial user study suggests that using an immersive VR offers benefits for the exploration task for the viewer and the user experience provided by VaRt-DataExplorer has received high ratings.