Reviewerly/exHarmony huggingface dataset:
Pengaruh Media Pembelajaran (Moodle Mobile Learning, LKS) dan Minat Peserta Didik terhadap Hasil Belajar Mata Pelajaran Administrasi Server

This research aimed to 1) measure the effect of learning media utilization and students interest on the learning outcome of server administration subject, 2) find out the impact of the interaction between learning media utilization and students interest on the learning outcome, 3) measure the effect between high learning interest and low learning interest using different learning media on the learning outcome. The research method was a pseudo experiment with 2x2 factorial research design, which meant comparing two groups: experiment group using moodle mobile learning media, and control group using student worksheet and distinguish students interest in low or high. Both groups were given pretest and post-test. The data was obtained through a questionnaire and a formative test. The data processing used two-way ANOVA and SPSS ver. 24 as a processing data aid.
PENDEKATAN Z-SCORE DAN FUZZY DALAM PENGUJIAN AKURASI PERAMALAN CURAH HUJAN

Determination of rainfall is important to determine the intensity of rain that occurs in an area. Rain intensity that is too high will certainly have a bad impact. Forecasting or prediction techniques are used to determine the likelihood of intensity occurring in the following year. However, rainfall data are continuous numerical data. Measurement of accuracy becomes more difficult if the data type is like that. So, this study tests the accuracy of rainfall forecasting in the city of Denpasar from a different perspective. This test combines the Z-score method and the Fuzzy set theory to normalize and classify rainfall data. This combination determines the degree of rainfall membership divided into Upper, Middle, and Lower levels. Based on the results of rainfall accuracy testing starting in 2012-2016 obtained an average value of accuracy of 85% with training data that is data in 2007-2015. The normalization process greatly affects the value of the training data.
THE IMPROVEMENT OF ENGLISH ABILITY THROUGH THE SINGING METHOD AT AR-RAUDHAH MUSTIA EDUCATION FOUNDATION, BATU MALENGGANG VILLAGE, LANGKAT DISTRICT

The community service activities are carried out in order that the students improve the English skills, especially for students at the Ar-Raudhah Mustia Education Foundation, Batu Malenggang Village, Langkat Regency. Its application is carried out by the singing method. Through the singing method taught, the students quickly absorb something that is taught and make a better mood. It is a way to achieve a goal in learning in a fun way. In this service, the tool used is the guitar.
Firmware Resiliency: Protection

Firmware resiliency includes three elements: protection, detection, and recovery. Protection means the protection of the firmware components from attacks. Protection is a proactive aspect of firmware resiliency, while detection and recovery are reactive mechanisms. For resiliency, the main threat is from both the software attacker and the hardware attacker.
Class Prediction by Prediction Intervals for Neural Nets

Generally, the unknown coefficients of neural nets are estimated by nonlinear least squares. Therefore, prediction intervals for the true value of the target feature exist. The paper proposes to use such intervals for class prediction and model selection. Only in this way, the uncertainty of class predictions can be indicated.
A Hybrid Approach of Texture Feature and Gradient Orientation for Computer Aided Diagnosis System Based on Breast Density Classification

A Computer-Aided Diagnosis (CAD) system can perform an accurate diagnosis and help radiologists by presenting a second opinion about breast density.However, the development of a robust CAD system for breast density classification is still an open problem.In this study, we proposed a CAD system based on hybrid intelligent machine learning technique for automatic classification of breast density on mammogram images.The proposed technique employs gradient orientation pattern HOG and texture descriptor CLBP-HF as features and K Nearest Neighbor (KNN) as classifier.The experiments were carried out on benchmarks public domain MIAS and DDSM datasets.The classification accuracy is 96.4% whereas recall and precision are 96.59 and 96.75% on MIAS dataset.Moreover, the comparison with the state-of-the-art breast density classification methods shows that the proposed method outperforms the existing methods on both MIAS and DDSM datasets, the improvement is significant on both datasets.The proposed method will help radiologists in assessing the breast density, which is important for breast cancer diagnosis.
Enjoyment of teaching and learning activities form methods in the system of secondary and higher vocational education in Volga region in the first half of the 20th century

Researched is continuity of secondary and higher vocational education’s system, gives is characteristic of the main teaching and learning activities’ methods in secondary and higher vocational educational institutions in the first half of the 20th century in Volga region. The choice of territorial framework is due to the fact, that Volga region is central one of Russia, the particularities of the system of secondary and higher vocational education’s development are typical for other regions of Russia. In the first half of the 20th century future specialists training’s methodological and methodological base and law-making execution of activities of secondary and higher vocational education institutions’ legal framework took place in Volga region, and that has determined the choice of chronological framework in this article. The authors address teaching and learning activities, used by teachers for learning process’s organization in Volga region’s educational institutions, pick out their advantages and disadvantages. The main methods are: “Dalton plan” with various forms of specially concerted activity, brigade-laboratory method, based on students’ work in team and tasks’ conduct independent operations, and comlpex method, formed up knowledge elicitation (for example, areas of interest and inclinations). Explanatory-illustrative methods of learning, procreational problem, partly search (heuristic), partly research (experimental) methods were used for preparing future specialists at universities.
Virtual Reality-Based Roller Coaster Simulation Development to Identify Cyber sickness and to Reduce its Effects

Cybersickness is one of the most significant barriers to using Virtual Reality (VR). Cybersickness consists of a series of unpleasant symptoms, such as eye fatigue, headaches, nausea, or even vomiting, caused by exposure to a virtual environment and can last from a few minutes to several days. It is estimated that around 20% to 80% of the total population experiences cybersickness to a certain extent. Based on these problems, a VR roller coaster simulation was developed to find out or to identify what caused cybersickness, and to reduce its effects. This simulation displays a roller coaster area that follows the track flow. Then there are the settings in the simulation to reduce the impact of cybersickness with several methods applied, and it is expected that the user can run the simulation longer. Based on the results of testing all methods proven to be able to reduce the effects of cybersickness and the best way to overcome its impacts is by increasing the FPS rate (from the developer side) and by taking Dimenhydrinate medicine (from the user side).
Authorized Deduplication of Encrypted data in Cloud

Cloud computing technology is rapidly developing nowadays. The number of files stored and processed is increasing per day. This increase brings severe challenge in requirement of space, processing power and bandwidth. More than half of the data generated in the cloud is duplicate data. To handle this data, deduplication technique is used which eliminates duplicate copies of data. This removal of duplicate data increases storage efficiency and reduce cost. In this paper, we propose secure role re-encryption system which allows authorized deduplication of data and also maintains privacy of data. This system is based on convergent algorithm and re-encryption algorithm that encrypts the user data and assign role keys to each user. This system grants privileges to users in order to maintain ownership of each user so that authorized users can access the data efficiently. In this system management center is introduced where the file is being encrypted and role keys are generated to handle authorized requests. Role keys are stored in Merkle hash tree which maps relationship between roles and keys. Authorized user who has particular role-encryption key can access the file. Convergent algorithm and role re-encryption algorithm allows access of specific file without leakage of private data. Dynamic updating of user privileges is achieved.
Analisis Kekuatan Bahan Pipa Ijuk Semen Berbasis Serat Ijuk Yang Bernilai Ekonomis

Abstract Water is the main support for human survival. Most frequently, the emergence of problems in the community environment is caused by the lack of clean water. Lack of clean water supply often occurs in rural areas, where residents cannot afford to buy PVC pipes and large pipes for water distribution, so we conducted a study and developed a simple method of making pipes, using materials that are easily available, and can be made by ourselves, which is a pipe with a mixture of palm fiber and cement. Using cement fibers should apply operational processes to water with good quality.
Experimental Framework to Simulate Rescue Operations after a Natural Disaster

Computational simulation is a powerful tool for performance evaluation of computational systems. It is useful to make capacity planning of data center clusters, to obtain profiling reports of software applications and to detect bottlenecks. It has been used in different research areas like large scale Web search engines, natural disaster evacuations, computational biology, human behavior and tendency, among many others. However, properly tuning the parameters of the simulators, defining the scenarios to be simulated and collecting the data traces is not an easy task. It is an incremental process which requires constantly comparing the estimated metrics and the flow of simulated actions against real data. In this work, we present an experimental framework designed for the development of large scale simulations of two applications used upon the occurrence of a natural disaster strikes. The first one is a social application aimed to register volunteers and manage emergency campaigns and tasks. The second one is a benchmark application a data repository named MongoDB. The applications are deployed in a distributed platform which combines different technologies like a Proxy, a Containers Orchestrator, Containers and a NoSQL Database. We simulate both applications and the architecture platform. We validate our simulators using real traces collected during simulacrums of emergency situations.
Method for Identifying PMU Bad Data Based on Long Short-Term Memory Network

Phasor measurement units (PMUs) have become one of the most effective tools for state awareness of power systems. However, the complex environment caused PMU data to have quality problems such as data loss, which seriously affected its applications in power systems. This paper proposes a method for identifying PMU bad data based on long short-term memory (LSTM) network. First, the advantages of LSTM in bad data identification are analyzed. Based on the advantages, a two-layer network is constructed, and a decomposition and reconstruction method for original data is proposed. On this basis, two objective functions are defined, and different error characteristics are obtained. A method for determining the threshold of bad data based on decision tree is proposed to realize the identification of bad data. The results by simulations and field data verified PMU data quality is improved, making it better applied to all aspects of the power system.
Practice Makes Perfect

Co-op placements are vital components of an LIS edcucation. Co-op programs allow students to gain relevant work experience, apply their theoretical knowledge of librarianship in the field, and identify new areas for professional development; however, one aspect is often overlooked in these programs. LIS co-op students can expand their experiential learning by proposing and pursuing new projects in the field, which will enhance their overall education and support their institution and profession at the same time. In this article, I will reflect on my co-op experience with the Collections and Content team at the University of Guelph, and I'll discuss how a group of co-op students started the first Co-op Community of Practice at Guelph.
Study Of Coliform And Escherichia Coli Bacteria Contamination In Part Of Gajahwong River Near Universitas Islam Negeri (Uin) Sunan Kalijaga Yogyakarta

The development of an area is indicated by an increase in the number of settlements. The activities of the UIN Yogyakarta campus have had an impact on the number of newcomers living temporarily and permanently around the campus. The negative impact is caused by the pollution of the Gajahwong River water from the disposal of domestic waste from the surrounding population. This study aims to examine the pollution of coli and  Escherichia coli  bacteria in the Gajahwong River fragment around the UIN campus in Yogyakarta. The research method was used in the form of field surveys and secondary data analysis of environmental monitoring results from the Yogyakarta Provincial Environment Office during the period of 2015 - 2019. The results showed that the number of stools and a total of coli bacteria were far above the quality standard. Both coli bacteria reach maximum conditions in 2019 and occur during the dry season
Pengembangan Bahan Ajar Simulasi Digital Bermuatan Model Edutainment untuk Menumbuhkan Keaktifan Belajar Siswa Kelas X TKJ di SMK Negeri 2 Turen

Based on an interview, 88% from 34 students received a score below the minimal completeness criteria in Digital Simulation subject because students were passive in the learning and the usage of uninteresting learning material. This developmental research aimed to design and develop the mobile-based digital simulation learning material to improve students' activeness in Class X TKJ, Public High School Vocational High School 2 Turen and tested the feasibility of teaching materials as learning supplements. This research used the ADDIE model, containing: (1) analyze, (2) design, (3) develop, (4) implement, and (5) evaluate. The feasibility test was performed in Class X TKJ students in Digital Simulation subject. Based on the obtained data, the material validation test from experts was 95%, media test from experts obtained 98.74%, small group test was 91.2%, and field test obtained 94.65%. It could be concluded that Simulation Digital learning material was in very feasible category.
Switching Probabilistic Slow Feature Analysis for Time Series Data

Slow feature analysis (SFA) is a machine learning method for extracting slowly time-varying feature from multidimensional time series data.Recently, probabilistic SFA (PSFA) that extends SFA to a probabilistic framework has been proposed.The PSFA can be applied to stationary time series data with noise and missing values.In order to deal with nonstationary time series data including change points, we propose a switching probabilistic slow feature analysis (switching PSFA) in this paper.By introducing a switching state space model, it is possible to extract slowly varying information even when system parameters change with time.Using the proposed method, we show that slowly time-varying components can be extracted more accurately from time-series data with non-stationarity.
New quasi-cyclic codes from finite upper half-planes

Finite upper half-planes can be seen as a natural environment to generate error-correcting codes. Current work analyses some properties of these spaces to generate new classes of quasi-cyclic error-correcting codes. These codes may be generated using the norm or the distance in these spaces. Using properties of the sets, we also propose a decoding algorithm.
The Effect of Substitution, Augmentation, Modification and Redefinition Model on Students’ Writing Skills

Purpose: This study aimed to determine the effects of Substitution, Augmentation, Modification and Redefinition (SAMR) Model on Danao National High School Grade 12 students’ writing skills. Specifically, it sought to determine if SAMR Model could enhance the writing skills of students.&#x0D; Approach/Methodology/Design: The study only covered the writing skills which include ideas, organization, word choice, sentence fluency and convention (grammar and mechanics). The written outputs, specifically the rationale, significance of the study and scope and delimitation from the students’ Practical Research 2 subject were the bases for the experimentation. The study utilized quasi-experimental method to determine the effectiveness of Substitution, Augmentation, Modification and Redefinition Model as the basis for technology integration on enhancing the students’ writing skills. This study used the researcher-made pre-test and post-test questionnaire and raters were chosen to evaluate students’ outputs.&#x0D; Findings: It was found out that the level of the writing skills of the control and experimental groups did not change on their pre-test and post-test. Both groups showed an increase on their post-test results. The results of the experimental group indicated that SAMR Model has improved students’ writing skills&#x0D; Practical Implications: The utilization of this model on writing activities or subjects will likely create a new field of interest and widen students’ perspectives on the different means or medium of writing. However, this tool would really take much time, effort and technological skills on the part of the facilitator to make it as effective as possible. &#x0D; Originality/value: This study proposed Action Program to Improve Writing Instruction in Danao National High School.
What You Need to Know About SOC 2 for Cloud Security

Migrating from your on-premise data center to cloud hosting options–public, private or hybrid—can feel like a big leap. A SOC 2 report provides peace ...
IMPROVING STUDENTS’ LISTENING COMPREHENSION THROUGH COOPERATIVE LISTENING

This research attempts to improve the students’ achievement on listening comprehension through cooperative listening. The research was conducted at the second grade by using classroom action research at the second grade students of SMA N 6 Medan. Four classes were selected as subjects that consist of 35 students. The students were taught cooperative listening meanwhile for the qualitative data, interview and observation were conducted. The quantitative data were collected by giving 10 multiple choice tests and calculating the mean. The result of the research shows that the mean of the second cycle (80.85%) was higher than the mean of the first cycle (68.28%). Based on the observation and interview, the students were becoming active and enthusiastic during the teaching learning processes.
Spontaneous and voluntary eyeblinks differentially affect target detection during continuous flash suppression

This study investigated how different types of eyeblinks, i.e., spontaneous (unintentional) and voluntary (intentional) eyeblinks, affect target detection during continuous flash suppression (CFS). CFS refers to a strong interocular suppression that can be produced by presenting a high-contrast dynamic pattern (suppressor) to one eye. In this study, we used breaking CFS paradigm in which after exclusive dominance of the suppressor had been established, luminance contrast of a target, which was presented to the other eye, was ramped up to its maximum (0.8) over 3.0 sec. The time required for target detection was measured. The suppressor was a color Mondrian pattern refreshed at 10 Hz, and the target was a Gabor patch (1.06 cpd, clockwise or counter-clockwise orientation, σ = 1°). Results showed that the detection time was longer when a spontaneous eyeblink occurred before target detection than when no blink occurred. However, time interval between an eyeblink and target detection was very variable, suggesting that spontaneous eyeblinks themselves did not affect target detection. By contrast, the detection time was shorter when a voluntary eyeblink was generated in response to a visual cue. Moreover, a close temporal relationship was found between a voluntary eyeblink and target detection; the detection time was peaked 0.5 sec after eyeblinks. Differential effects of spontaneous and voluntary eyeblinks on target detection suggested that a transient change in a retinal image caused by eyeblinks did not play a critical role in modulating target detection. Consistently, a physical blackout, which was produced by darkening the stimulus display and had timing and duration comparable to eyeblinks, did not affect target detection. Furthermore, we also found that the detection time was shorter when voluntary eyelid opening was generated. Collectively, the present findings suggested that extra-retinal processing associated with voluntary eyelid movements facilitates target detection during CFS.
Surveillance of operation theatres of a tertiary care hospital by settle plate method and surface swab technique

Surveillance of operation theatres of a tertiary care hospital by settle plate method and surface swab technique - IJMR- Print ISSN No: - 2394-546X Online ISSN No:- 2394-5478 Article DOI No:- 10.18231/j.ijmr.2020.044, Indian Journal of Microbiology Research-Indian J Microbiol Res
RETRIEVING STEREO IMAGE USING VISUAL WORD PAIRS WITH CONVOLUTION NEURAL NETWORK

The exponential increase and omnipresent access to visual data on the Internet contributed to the growth of image search or recovery science.Ignoring the visual content as a ranking indicator can result in inconsistencies between the words and the visual content with the selection technique.The failure of current methods and characteristics of HrosSIs therefore does not provide a reasonable retrieval of images.In addition, nothing of the recent remote sensing image retrieval techniques takes the basic features of highresolution optical satellite stereo images (HrosSIs) such as the display number and the viewing angles into account.The article offers a specific structure to leverage the unique features of HrosSIs data in such a way that HrosSI's information is collected efficiently and accurately.The recovery of HrosSI is achieved through the similitude among the structures attained from DSMs and orthographs, together mined from the HrosSIs.Moreover, the value of pinnacle evidence stood examined for HrosSI recovery.For process authentication spending the ISPRS stereo test dataset, a prototype framework has been developed and implemented.Investigational results demonstration that the methods projected for HrosSI recovery are successful.The proposed system is successful and tailored to stereo images conveyed across space but may also be sufficient for stereo images transmitted by air.