Reviewerly/exHarmony huggingface dataset:
Reliability Analysis of Risk Model Metrics Based on Business Approach in Information Security

Threat of information security has impact to business of organization.Therefore, the development of information security risk model should consider business perspective.In order to develop new risk model, defining metrics is important process.It can be conducted by theoretical analysis, validity analysis and reliability analysis.Theoretical analysis and validity analysis had been performed in previous work.Furthermore, reliability analysis is performed in this paper.Cronbach's Alpha is required as method to measure reliability coefficient from five proposed metrics namely reputation, financial impact, critical level, business type of organization, and size of organization.Reliability analysis from proposed metrics results coefficient between 0.70-0.91.Based on previous researches, metric is reliable if it has coefficient greater than 0.65.Therefore, proposed metrics have adequate reliability to be used as metrics of risk model.
A Committee of Convolutional Neural Networks for Image Classification in the Concurrent Presence of Feature and Label Noise

Image classification has become a ubiquitous task. Models trained on good quality data achieve accuracy which in some application domains is already above human-level performance. Unfortunately, real-world data are quite often degenerated by noise existing in features and/or labels. There are numerous papers that handle the problem of either feature or label noise separately. However, to the best of our knowledge, this piece of research is the first attempt to address the problem of concurrent occurrence of both types of noise. Basing on the MNIST, CIFAR-10 and CIFAR-100 datasets, we experimentally prove that the difference by which committees beat single models increases along with noise level, no matter whether it is an attribute or label disruption. Thus, it makes ensembles legitimate to be applied to noisy images with noisy labels. The aforementioned committees’ advantage over single models is positively correlated with dataset difficulty level as well. We propose three committee selection algorithms that outperform a strong baseline algorithm which relies on an ensemble of individual (nonassociated) best models.
USING OF PhET–INTERACTIVE SIMULATION IN TEACHING OF GENERAL CHEMISTRY TO PHARMACEUTICAL STUDENTS IN HIGHER EDUCATION ESTABLISHMENT

The problems and prospects of using virtual simulators for increasing the interactivity of educational materials in teaching general and inorganic chemistry in higher educational institutions are considered. The virtual practical works in general chemistry with the use of PhET’s simulations by pharmacist students were tested in accordance with the developed protocols and instructions. The advantages and disadvantages of the virtual practical works on the PhET–Interactive Simulation (http://phet.colorado.edu) are formulated. Performing practical tasks on the PhET simulators enhances the quality of knowledge. It is established that the use of PhET simulations is an effective method of interactive learning, which helps to improve the learning of material in both traditional lectures and demonstrations, as well as in practical classes. Students have a growing cognitive interest in real experiment, developing research and experimental competencies, in particular, the ability to formulate and ask questions, make predictions, use evidence to support ideas, focus on the main details, choose the optimal algorithms for the experiment, develop facility with commonly-used scientific representations and measurement tools, coordinate across scientific representations, science models, and real world situations. Students study to identify cause-effect relationships, make connections to everyday life. PhET simulations provide students with the opportunity to work with new material and develop further interest in science, however, the effectiveness of learning depends not only on the PhET, but also on whom and where it is used, how it is integrated into the learning process. PhET–-Interactive Simulations are effective for students to develop the skills and competencies needed to master the following chemical disciplines.
TGSIFT: Robust SIFT Descriptor Based on Tensor Gradient for Hyperspectral Images

This paper proposes a robust sparse descriptor based on tensor theory by using the spatial and spectral information synthetically, namely the Tensor gradient SIFT (TGSIFT), for Hyperspectral image (HSI). TGSIFT integrates both spatial and spectral information and considers the natural vector feature of HSIs. Based on the HSI Gaussian scale space, a new tensor model for HSI is proposed which takes the vectorial nature of HSI into consideration and preserves all the necessary structural information distributed over all the bands. The TGSIFT descriptor is formed based on the model proposed. Experimental results of HSI matching show that the TGSIFT descriptor achieves better matching performance than other SIFT descriptors under different transformations, including illumination change, sensor noise, image rotation, viewpoint change, and scale change.
A Hybrid Recommender System for Rating Prediction of Arabic Reviews

Recommender systems nowadays are playing an important role in the delivery of services and information to users. Sentiment analysis (also known as opinion mining) is the process of determining the attitude of textual opinions, whether they are positive, negative or neutral. Data sparsity is representing a big issue for recommender systems because of the insufficiency of user rating or absence of data about users or items. This research proposed a hybrid approach combining sentiment analysis and recommender systems to tackle the problem of data sparsity problems by predicting the rating of products from users’ reviews using text mining and NLP techniques. This research focuses especially on Arabic reviews, where the model is evaluated using Opinion Corpus for Arabic (OCA) dataset. Our system was efficient, and it showed a good accuracy of nearly 85% in predicting the rating from reviews.
Coal Mine Geology Digitization Management System Development

Abstract Geological data information is the important foundation of the mining engineering design and production management. According to the mining engineering of mine geological information management and processing requirements, it established mine geological information database and geological model by using the unified management model of relational data and graphic data. Through geological data management module and the geological mapping management module, it can realize the comprehensive functions of collecting and managing basic geographic data, drilling data, the underlying data of bedrock geology, the underlying data of engineering geology. Automatically set up the integrated graphicsgeological of model and geological data.
Sight-reading as an important factor in the professional growth of future music teacher

The aim of the following study is to highlight the significance of the development of sight- reading skills both in the higher stages of music education implemented in the university, conservatory, and in the music career of performer-teachers. The author has examined a large number of Soviet, Post- Soviet and Western studies concerning the topic with sufficient practical recommendations and methods for developing this skill. According to the results of the online questionnaire-based survey, carried out among participants, the data analyses showed that, in spite of giving importance to sight-reading, the respondents seek to pay more attention to this skill by involving it in the curricula on their own initiative. As a result, the author's hypotheses are fully supported. Besides, based on her own experience, the author confirms that sight- reading provides the music teacher with a broad range of benefits leading to professional development and a good reputation among the students.
IMPACT OF EXPORTS AND IMPORTS ON THE ECONOMIC GROWTH IN BURUNDI

This paper investigated the impact of exports and imports on the economic growth in Burundi. To achieve this purpose, annual data for the periods between 1989 and 2018 were tested. The study used Granger Causality and Johansen Co-integration approach for long-run relationship Using Augmented Dickey-Fuller (ADF) and Phillip-Perron (PP) stationarity test, the variable proved to be integrated of the order I(1) at first difference. Johansen and Juselius Co-integration test was used to determine the presence or otherwise of a co-integrating vector in the variables. To find out the direction of causality among the variables, at least in the short-run, the Pairwise Granger Causality was carried out. Exports were found to Granger Cause imports. The results show that there is unidirectional causality between exports and imports. These results provide evidence that growth in Burundi was propelled by a growth-led import strategy as well as export-led import. Imports are thus seen as the source of economic growth in Burundi. KEYWORDS: Co-integration, Granger causality; Exports; Imports; Economic growth, Burundi.
A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets

&lt;span&gt;Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. However, real world applications commonly involved imbalanced class problem where the classes have different importance. This condition impeded the entropy-based heuristic of existing ATM algorithm to develop effective decision boundaries due to its biasness towards the dominant class. Consequently, the induced decision trees are dominated by the majority class which lack in predictive ability on the rare class. This study proposed an enhanced algorithm called hellinger-ant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. The proposed algorithm was compared to the existing algorithm, ATM in nine (9) publicly available imbalanced data sets. Simulation study reveals the superiority of HATM when the sample size increases with skewed class (Imbalanced Ratio &amp;lt; 50%). Experimental results demonstrate the performance of the existing algorithm measured by BACC has been improved due to the class skew-insensitiveness of hellinger distance. The statistical significance test shows that HATM has higher mean BACC score than ATM.&lt;/span&gt;
An Acquisition Method for Visible and Near Infrared Images from Single CMYG Color Filter Array-Based Sensor

Near-infrared (NIR) images are very useful in many image processing applications, including banknote recognition, vein detection, and surveillance, to name a few. To acquire the NIR image together with visible range signals, an imaging device should be able to simultaneously capture NIR and visible range images. An implementation of such a system having separate sensors for NIR and visible light has practical shortcomings due to its size and hardware cost. To overcome this, a single sensor-based acquisition method is investigated in this paper. The proposed imaging system is equipped with a conventional color filter array of cyan, magenta, yellow, and green, and achieves signal separation by applying a proposed separation matrix which is derived by mathematical modeling of the signal acquisition structure. The elements of the separation matrix are calculated through color space conversion and experimental data. Subsequently, an additional denoising process is implemented to enhance the quality of the separated images. Experimental results show that the proposed method successfully separates the acquired mixed image of visible and near-infrared signals into individual red, green, and blue (RGB) and NIR images. The separation performance of the proposed method is compared to that of related work in terms of the average peak-signal-to-noise-ratio (PSNR) and color distance. The proposed method attains average PSNR value of 37.04 and 33.29 dB, respectively for the separated RGB and NIR images, which is respectively 6.72 and 2.55 dB higher than the work used for comparison.
The Utilization of Blogs In Education

Blog comes from the word "Weblog" which was shortened to blog.The term Blog was introduced by Jorn Barger in 1997.The blog is one of the services provided by the internet service so users can read or write a wide variety of content that they want.It can be reached through two creation methods i.e. through the Blog Service and Blog engines.Blog Engine is more intended for a master of language programming in web creation, while for a beginner it is recommended to use Blog Service as a method of making blog.By utilize the blog as a medium for delivering education from an educator or an educational institution can convey knowledge in a different view than usual and certainly will not make readers who incidentally as learners and the wider community was quickly bored in reading.The appearance of a blog and eye-catching view can also be a solution to foster the habit of rading in the community.
Histology Study in Undergraduate Medical Education

Histology is an essential field in the education of medical students, and competent knowledge in histology is very important when studying pathology. Current teaching methods for histology in medical schools involve using a conventional light microscope (CM) with or without a virtual microscope (VM). This review aims to present advantages and disadvantages of using CM and VM in terms of teaching and learning histology in the context of undergraduate medical education. One major advantage of the traditional CM histology learning method in laboratory practice is that this allows students to practice using a light microscope; however, study flexibility is limited as the students cannot take the microscope back home for self-study after the histology class has finished. Costly repairs and maintenance must also be considered when using CM. By contrast, VM technology can provide flexibility and convenience for both students and staffs. This method allows students to both self-study and group-study almost anywhere at any time. This review emphasizes that histology learning in undergraduate medical education using VM is no longer confined to the classroom. However, the basic skill of how to operate a conventional light microscope is still important for medical students because CM is commonly used in the hospital laboratories and some hospitals may not be equipped with VM technology.&#x0D;
Klasifikasi Kain Songket Lombok Berdasarkan Fitur GLCM dan Moment Invariant Dengan Teknik Pengklasifikasian Linear Discriminant Analysis (LDA)

Songket is one of Indonesia's cultural heritage that is still present today. One of the most famous songket woven fabrics is the Lombok songket. Lombok songket has diverse, unique, and beautiful motifs. However public knowledge of Lombok songket motifs is still minimal and the difference between one motif with another is still unknown. The lack of digitalized data collection is one reason for this. Therefore, we need a system that can classify the Lombok songket automatically. In this study, a system was developed based on texture features and shape features using Linear Discriminant Analysis (LDA). The GLCM method is used in the texture feature extraction process and the Invariant Moment method is used in the feature extraction process. The total data used in this study is 1000 images from 10 Lombok songket motifs which are divided into training data and test data. The highest accuracy is obtained on the Invariant Moment and GLCM feature with an image resolution of 300x300 pixels using the most effective feature that is equal to 96.67%.
Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases

Many applications of machine learning on discrete domains, such as learning preference functions in recommender systems or auctions, can be reduced to estimating a set function that is sparse in the Fourier domain. In this work, we present a new family of algorithms for learning Fourier-sparse set functions. They require at most nk − k log k + k queries (set function evaluations), under mild conditions on the Fourier coefficients, where n is the size of the ground set and k the number of non-zero Fourier coefficients. In contrast to other work that focused on the orthogonal Walsh-Hadamard transform (WHT), our novel algorithms operate with recently introduced non-orthogonal Fourier transforms that offer different notions of Fourier-sparsity. These naturally arise when modeling, e.g., sets of items forming substitutes and complements. We demonstrate effectiveness on several real-world applications.
A Preliminary Usability and Universal Design Evaluation of a Television App User Interface

This paper details a two-part evaluation of the Apple TV user interface.A Heuristic Evaluation and an evaluation using the seven universal design principles were carried out.The overall results showed that the Apple TV user interface has various failings in the design for users of diverse kinds.Suggestions for ways forward include designers using more rigorously the ISO standards and well established user interface design guidelines.
USING STORY MAPPING TECHNIQUE IN TEACHING READING OF NARRATIVE TEXT FOR JUNIOR HIGH SCHOOL STUDENTS

This paper is aimed at describing the use of ‘Story Mapping’ to improve students’ comprehending in reading narrative text at junior high school students. This technique is applied to help junior high school students to understanding andcomprehending narrative text. This technique enables students to solve the problem by using story mapping sheet given to them. By using this technique, the students are allowed to read the narrative text and determine the appropriate part of the text to each part of the sheet on story mapping.
Some Remarks on Replicated Simulated Annealing

Abstract Recently authors have introduced the idea of training discrete weights neural networks using a mix between classical simulated annealing and a replica ansatz known from the statistical physics literature. Among other points, they claim their method is able to find robust configurations. In this paper, we analyze this so called “replicated simulated annealing” algorithm. In particular, we give criteria to guarantee its convergence, and study when it successfully samples from configurations. We also perform experiments using synthetic and real data bases.
Penerapan Konsep Learning Commons sebagai Upaya dalam Revitalisasi Layanan di Dinas Kearsipan dan Perpustakaan Provinsi Sumatera Barat

AbstractThis research aims to describe (1) the form of the application of the learning commons concept in the Archives Service and Library West Sumatra Province; (2) the concept of learning commons in the Archives and Library of West Sumatra Province; (3) efforts to realize learning commons in the Archives and Library of West Sumatra Province; and (4) factors that must be considered in applying the concept of learning commons. This study uses a descriptive method with a qualitative approach, which is collecting data by conducting observations and interviews with librarians and library users in the Archives Service and Library West Sumatra Province. The results of the research that have been carried out show, First, the form of the application of the concept of learning commons in the Archives and Library of West Sumatra Province is applied in information technology, namely by using the INLISLite application to provide technology-based services as well as maximum utilization of library space and facilities. Second, there are three concepts of learning commons that exist in the Archives and Library of West Sumatra Province, namely, the concept of learning, the concept of discussion, and the concept of information technology. Third, the efforts made in realizing learning commons in the Archives Service and Library of West Sumatra Province are influenced by the performance of librarians in the Archives and Library West Sumatra Province. Fourth, there are seven factors that must be considered in implementing the concept of learning commons, namely, user-centered, flexible, repetitive questions, join resources, delete remove barriers, trust your users, and publicize. All these factors have been carried out by the Office of Archives and Library of West Sumatra Province although there are still some applications that have not been maximized.Keywords: library; concept; learning commons.
Penerapan Metode Kauny Quantum Memory dalam Meningkatkan Hafalan dan Pemahaman Siswa Pada Pembelajaran Tahfiz di MI Nurul Qomar Palembang

The problems that occur in Tahfiz learning at MI Nurul Qomar are memorization and students' understanding in the memorization process is still low, so we need a method that allows students to memorize. The purpose of this study was to improve students' memorization and understanding of the Kauny Quantum Memory method in the process of learning to memorize students at MI Nurul Qomar Palembang. This type of research is field research using quantitative research approaches and the design used is quasi-experimental. Data collection is done by oral tests, interviews, observations, and documentation, data analysis using T tests. The findings in this study are that learning Tahfiz in MI Nurul Qomar Palembang by applying the Kauny Quantum Memory method has a significant effect. This is evidenced by the hypothesis test that uses the t test, the value of t_count is obtained = 4.112 while ttable = 2.09. Therefore it can be concluded that t_count&gt; t_table or 4,112&gt; 2.09. Because t_calculate = 4.112 is greater than the price of ttable = 2.09 at a significant level of 5% with degrees of freedom n-2 (22-2 = 20). So H_o which states there is no significant influence with the application of the Kauny Quantum Memory method in improving students 'memorization and understanding in Tahfiz learning at MI Nurul Qomar Palembang is rejected, while H_a which states there is a significant influence with the application of the Kauny Quantum Memory method in improving students' memorization and understanding in Tahfiz learning at MI Nurul Qomar Palembang is accepted. So, the Kauny Quantum Memory learning method can be said as one of the effective learning methods to improve memorization and understanding of the Koran of students at MI Nurul Qomar Palembang.&#x0D;
The Effectiveness of Visualization, Auditory, Kinesthetic (VAK) Model toward Writing Narrative: Linguistic Intelligence Perspective

This research was a quasi-pretest-posttest design experimental study with experimental and control classes.The experimental class applied the VAK model and the control class applied the guided inquiry model.The research was conducted on fifth-grade students of primary schools in Surakarta in the academic year 2018/2019 with a sample of 114 students selected by random sampling technique.The research data was obtained by a narrative writing test instrument that had been validated by linguists and evaluation experts before tested.The results showed the mean score of narrative writing skills gained in the experimental class was 0.44 compared to the control class of -0.30.The results of the independent sample t-test showed a significant difference between the experimental class and the control class with a t-value of 25.155 and a sig.(2tailed) value of 0.000 <0.05.The effect-size calculation showed that the VAK model had a high effectiveness in learning narrative writing skills, with a value of d = 7.58.Based on the theory, related to learning style (visualization, auditory, kinesthetic) could enhance the increase in linguistic intelligence as an internal factor affecting narrative writing skills.Based on research findings and theories, it can be synthesized that in terms of linguistic intelligence, the VAK model is effective in improving narrative writing skills.