Reviewerly/exHarmony huggingface dataset:
Mapping of Intrusive Complex on a Small Scale Using Multi-Source Remote Sensing Images

Multi-stage intrusive complex mapping plays an important role in regional mineralization research. The similarity of lithology characteristics between different stages of intrusions necessitates the use of richer spectral bands, while higher spatial resolution is also essential in small-scale research. In this paper, a multi-source remote sensing data application method was proposed. This method includes a spectral synergy process based on statistical regression and a fusion process using Gram–Schmidt (GS) spectral sharpening. We applied the method with Gaofen-2 (GF2), Sentinel-2, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to the mapping of the Mountain Sanfeng intrusive complex in northwest China in which Carboniferous intrusions have been proven to be directly related to the formation of Au deposits in the area. The band ratio (BR) and relative absorption band depth (RBD) were employed to enhance the spectral differences between two stage intrusions, and the Red-Green-Blue (RGB) false colour of the BR and RBD enhancement images performed well in the west and centre. Excellent enhancement results were obtained by making full use of all bands of the synergistic image and using the Band Ratio Matrix (BRM)-Principal Component Analysis (PCA) method in the northeast part of the study area. A crucial improvement in enhancement performance by the GS fusion process and spectral synergy process was thus shown. An accurate mapping result was obtained at the Mountain Sanfeng intrusive complex. This method could support small-scale regional geological survey and mineralization research in this region.
Data Classification with Deep Learning Using Tensor Flow

Handwritten digits recognition is method of recognizing and classifying handwritten digits from 0 to 9. We have implemented recognizing hand written digits in a better and accurate approach to identify manually written digits from 0 to 9. For this we have used a multilayer sustain forward system called Convolutional network is taken into consideration.We have used Tensorflow, one of the most popular deep learning libraries to classify MNIST dataset, which is frequently used in data analysis studies.By Using Tensorflow, CNN has achieved an accuracy of 99% on data.The functions used for implementing the digit recognition are Rectified Linear Unit (ReLu), Hyperbolic Tangent (tanH), Exponential Linear Unit (eLu), sigmoid, softplus and softsign.In this Study, Convolutional Neural Network (CNN) and SoftMax classifier are used as deep learning artificial neural network.The results show that the most accurate classification rate is obtained with the use of the ReLu activation function.
Sistem Pakar Menggunakan Metode Certainty Factor untuk Estetika Kulit Wanita dalam Menjaga Kesehatan

The skin is an important organ located on the outside of the human body that needs to be kept healthy. Good skin health will certainly increase self-confidence, especially for women. Lack of information about diseases and treatment solutions and the small number of professional estheticians means that women end up not consulting when skin problems arise. If left untreated, skin problems will be more serious. The purpose of this study was to identify the accuracy of skin problems in women so that a solution in caring for the skin was obtained. The data processed in this study are the results of an interview from an aesthetic doctor about skin problems in women and the solutions and symptoms experienced by patients. Then the data obtained manually were processed using the Certainty Factor method and tested with a website-based system. The processing stage of this method is the compilation of symptoms into rules, giving weight values ​​for each symptom and calculating based on the Certainty Factor rule formula. The results of testing this method were 13 data on aesthetic skin diseases identified from 15 trial data. So that the level of accuracy is 86.67%. The results of this test have been able to identify well. The Certainty Factor method used can identify quite specifically and can be recommended to skin aesthetic doctors in increasing accuracy for identifying skin problems in women.
PERBANDINGAN KLASIFIKASI ALGORITMA C5.0 DENGAN CLASSIFICATION AND REGRESSION TREE (STUDI KASUS : DATA SOSIAL KEPALA KELUARGA MASYARAKAT DESA TELUK BARU KECAMATAN MUARA ANCALONG TAHUN 2019)

Decision tree is a algorithm used as a reasoning procedure to get answers from problems are entered. Many methods can be used in decision trees, including the C5.0 algorithm and Classification and Regression Tree (CART). C5.0 algorithm is a non-binary decision tree where the branch of tree can be more than two, while the CART algorithm is a binary decision tree where the branch of tree consists of only two branches. This research aims to determine the classification results of the C5.0 and CART algorithms and to determine the comparison of the accuracy classification results from these two methods. The variables used in this research are the average monthly income (Y), employment (X1), number of family members (X2), last education (X3) and gender (X4). After analyzing the results obtained that the accuracy rate of C5.0 algorithm is 79,17% while the accuracy rate of CART is 84,63%. So it can be said that the CART method is a better method in classifying the average income of the people of Teluk Baru Village in Muara Ancalong District in 2019 compared to the C5.0 algorithm method.&#x0D; &#x0D; Keywords: C5.0 Algorithm, CART, Classification, Decision Tree.
Level Kemampuan Literasi Matematis Pada Buku Tematik Terpadu Untuk Siswa Kelas 6 Tema Selamatkan Makhluk Hidup

This study aims to determine the level of mathematical literacy skills in the integrated thematic book on the theme of saving creatures in grade 6 used by the students. This research approach is descriptive qualitative and the type of research is literature. Primary data sources are integrated thematic books on the theme of saving living beings in grade 6 and secondary data sources are references to support students' mathematical literacy abilities. The data processing technique is done by editing, organizing, and drawing conclusions. The data analysis technique used is the content analysis which aims to provide systematic and printed written information and discussion. The results showed that the mathematics literacy skills of students in grade 6 SD were at level one, two, and three. Level three explains that students can carry out procedures clearly, including procedures that require sequential decisions.
Method to Grasp a Feeling of Being There by Turning a Head Forcibly while Watching a Tourism Video using a VR Headset

In virtual reality (VR) tourism, when watching a video of a tourist location, the feeling of presence improves the experience. Furthermore, it is desirable to be able to give a feeling of having been there before to the users visiting the site afterward. In this study, we aimed to reveal the factors that provide these feelings. We hypothesized that one of the factors is the perception of self-motion. Therefore, we proposed a method wherein the users were induced to turn their heads to the left and right when watching the video of a tourist site via a VR head-mounted display. We conducted two experiments and found that the proposed method conveyed the greatest sense of presence. On the other hand, there was no significant difference in giving the feeling of having been there between the proposed method and watching the video of the site on a PC.
Usability Aspects Related to the Use of M-Learning in Elementary Schools in Palestine

Learning Chemistry course is considered as a difficult task for many learners especially for elementary school students. This is related to understanding different concepts chemical reactions atoms structures, physical representations of molecules, etc. One way to facilitate the learning process of chemistry course is to use Mobile Learning (m-learning) technology. M-learning has different added values compared to classical learning materials such as text book, pictures, etc. Among the different added values of using mobile in educational contexts is the fact that smartphone has richer interaction techniques. Furthermore, smartphones and tablets PC are considered as more attractive for students. Also, there has been a rapid growth in the mobile technology concerning hardware and software. Accordingly, with the widespread use of smartphones and tablets, researchers start investigating the use of such devices in different educational contexts. The use of mobile learning is considered as a recent trend in Palestinian elementary schools and there is a minimal research attention has been directed to the student’s attitudes and satisfaction in using m-learning in their learning process. Therefore, our work aims at investigating the use of m-learning by students in elementary schools in Palestine. In particular, we focused on female students as in general female students show less interest in science and technology than male students. We were keen to investigate whether the use of m-learning could change this attitude. Therefore, an educational mobile application called ChemApp was developed to help learners to learn different concepts in chemistry course such as elements’ order in the periodic table, electronic distribution, atomic and mass numbers, chemical bonds and formula. By using the ChemApp, the students are able to interact with different components to explore the possible reactions in an interactive interface, to understand the structure and shape of atoms and molecules. The ChemApp was evaluated by a class of 13-14 years old (8th grade) students in a Palestinian primary school. The total number of participants was 30 female students. After analyzing the results, we conclude that these female students had a positive attitude toward the use of m-learning in their learning process of chemistry course. The results of this research work can be considered by policy and decision makers in educational institutions.
Implementation of Agile Methodology in Developing Countries: Case Study in Lebanon

Researchers have become interested in agile approaches to information systems development, because of their potential to improve product quality and increase productivity. While often associated with project orchestration in software development, agile methods have a wider potential application within ICT4D. Our interest, in this research, is to explore how practitioners in developing countries describe factors that either enable or impede the adoption of agile information system development methods. We chose Lebanon to investigate this question, because it is a center for outsourcing software development in Middle Eastern countries. We employed a qualitative research approach by conducting 31 semi-structured recorded interviews with practitioners in three Lebanese software development companies. We employ an analytical model which interlinks institutional theory, the capability approach, and ICTs to explore creating software using agile methodology. The analysis revealed positive reinforcement between three factors that improve the effectiveness of agile methods including the inclusive and detailed sprint planning, rich variety of stakeholder communication tactics, and teams that embrace a rich variety of communication technologies that overcome challenges presented by geographical distance. On the other hand, we also discovered impediments to agile adoption including team and management misunderstandings of agile methodology and the current political and economic crisis in the country. The model revealed the low investment of companies in ICT. The lack of knowledge of agile ceremonies roles and artefacts created gaps in the implementation process. Also, the model highlighted bottlenecks that should be crucially tackled such as the lack of customer involvement and risk mitigation towards external factors.
Models of Propagation of Inside Information

Insider trading is the buying or selling of a publicly traded company's stock by someone who has non-public, material information about that stock.The following article presents an innovative model which could help to solve the major problem of effective detection of insider trading.According to our research, the simultaneous occurrence of an increased volume and price changes without the occurrence of other disturbing factors (e.g., earlier company reports) allows to strongly suspect the occurrence of insider trading.This means that a significant increase in transaction volume is a better indicator of the likely insider trading than a price change alone.By analysing the disclosed case of insider trading on Drewex shares in 2010 we tested the effectiveness of our model and we came to the conclusion that the probability of insider trading in Drewex SA shares was 70%.
Estimation of Photovoltaic Energy Conversion Using Mixed Weibull Distribution

The uncertainty in the potential of electricity generation, due to the natural variation of solar radiation as daily changes, is one of the important challenges for the photovoltaic technology.This paper presents a stochastic modeling and analysis of the measured electrical parameters of a photovoltaic system, irradiance and the power generation under a spring day at Boumerdes location (Algeria).A comparison study between the sunny day and cloudy day is introduced to show the effect of the variation of irradiance and the temperature on the energy conversion.Stochastic modeling and analysis are made using mixed Weibull distribution, its parameters are estimated based on the maximum likelihood method.The obtained results in this work are; the estimated mean values of the irradiance, the power generation of the PV system, and the cumulative probability function of the energy conversion.The mean objective is to predict a generated power, for the adequate design and sizing of the PV array.
Dysphemism Lexical Items of Hate Speeches: Towards Education of Students for Political Correctness

This paper aimed at identifying and organizing any dysphemism lexical items used by people in disseminating hate speech expressions through Social Media posts and also teaching the political correctness to the students in order to avoid the use of hate speech items in their daily encounters especially in terms of using social media.This was qualitative study which described the use of nine dysphemism types of the hate speech on social media based on seven Indonesian Supreme Court's decisions.Observation, note-taking, and substitution techniques were used to collect the data from the Indonesian Supreme Court's decision by using purposive sampling technique.In order to analyze the data, the first step was organizing data, then followed by transcribing and converting the result of note-taking into text data and finally organizing them into the nine types of dysphemism.The result of the study showed that there are 32 words/phrases found in seven decisions of hate speech on Social Media contents concerning nine types of dysphemism.Most hate speeches on the Social Media contents are found in "-ist" dysphemism type within 15 words/phrases (46.875%), then followed by synecdoche -10 words/phrases (31.25%), dysphemistic epithets (4 words/phrases or 12.5%), and name dysphemism with 3 words/phrases (9.375%).Meanwhile, there are no words or phrases which related to the rest five types of dysphemism; euphemistic dysphemism, dysphemistic euphemism, homosexual dysphemism, non-verbal dysphemism, and cross-cultural dysphemism.
T-Distributed Stochastic Neighbor Embedding with Gauss Initialization of Quantum Whale Optimization Algorithm

T-distributed stochastic neighbor embedding is an important nonlinear dimensionality reduction algorithm in manifold learning, which has great application value in big data, data mining, machine learning, deep learning and other fields. The essence of its algorithm is to solve the minimum value problem of KL divergence. Because KL divergence is a convex function, gradient descent method or stochastic gradient descent method are often used to solve it. However, the global convergence of gradient dependent method is poor, so the main purpose of this paper is to introduce the quantum whale optimization algorithm with Gaussian initialization into the optimization part of t-SNE.
Teaching Reform of the Course of Automatic Control Theory Based on Engineering Cases

Based on enriching the teaching resources and improving the quality of classroom teaching, combined with the current curriculum standards, class hours, teaching materials and other specific requirements, the construction of the engineering case database of the course of automatic control principle is carried out, and the engineering case is applied to classroom teaching practice, the traditional classroom teaching mode is reformed, and the project-based and discussion based teaching is carried out based on the engineering case to improve the teaching effect.This paper puts forward the specific methods and approaches for the construction of the engineering case resource base, studies the selection, processing design and optimization scheme of the engineering case according to the needs of the specific teaching content, and the completed engineering case has been used in the teaching practice of the automatic control principle course, which has played a positive role in promoting the quality of personnel training.
Transformation of copyright limitations in the digital age

Founded in 1957, “Pravovedenie” (until 2018 know as “Proceedings of Higher Educational Institutions. Pravovedenie”) is one of the oldest and most authoritative academic peer-reviewed legal journals in Russia.
A Novel Method for Achieving Minimum Distance Collision-free Tool Path for Drilling

In recent years, many researchers have studied drilling tool path generation.Tool travelling time is a major portion of overall manufacturing time particularly in large scale items to be drilled.Nowadays, tool path is selected from a set of regular tool paths offered in CAM systems.These tool paths are mostly far from being the optimum path.In this paper, a new Travelling Salesman Problem (TSP) is utilized for generating a safe tool path in drilling processes.The developed optimization model can handle the objective function under multiple constraints, namely, returning to the tool origin rather than the initial hole to be drilled, considering all workpiece dimensions/corners for the initial position of the drill bit, as well as an obstacle constraint to generate a collision free trajectory.Performance of the proposed model is obtained for different initial tool positions on all corners of the workpiece.The results prove that the model can solve the problem in a timely manner and is able to generate an optimum safe path for tool traverse.
Laboratory Blood Coagulation in Sudanese with Falciparum Malaria: A Glance of Change Outcomes

is switched to humans (host) by the snap of an infected female Anopheles mosquito.Most human infections occur by P. falciparum and P. vivax, and limited degree to P. ovale, P. malariae, and P. knowlesi additionally infect human [3].The causative agent of the acute form of malaria is P. falciparum which is responsible for the highest morbimortality rates [4].Most of the mortality rates were in Africa (90%), followed by Southern East Asia (7%), and (3%) in the eastern Mediterranean area [5].Malaria in Sudan is considered a major public health problem and accounted for 37% of all maternal mortality [6].Malaria parasite (Plasmodium) overruns red blood cells as part of its asexual turn in the host (human).The Plasmodium matures in the erythrocytes to trophozoites and schizonts, then they disappear from the blood and stationed specifically in the vascular beds, this mechanism is called sequestration [7].Abnormal bleeding is regarded as one of the major manifestations of P. falciparum malaria [8].Plasmodium pathogenesis has been associated with both endothelial activation and injury in uncomplicated or fatal cases of malaria.However, the molecule receptors like E-selectin, P-selectin, intracellular adhesion molecules-1 (ICAM-1), and tissue factor (TF) have been stated in a previous study [9].Importantly, malarial infection has been classified into mild, moderate, and severe according to the rate of parasitemia [10].In regard to laboratory hemostasis, malaria infection changes are not in fact the same in all studies [11], which might be due to severity of infection and/or selection of the patients.Coagulation disorders and thrombocytopenia are commonly seen in
Turbid of Water By Using Fuzzy C- Means and Hard K- Means

In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.
Quality of agile adoption in global software development: An assessment model

&lt;span&gt;Over the last decade, software development has faced two approaches to Agile and global software development (GSD). While Agile development is focused on the reduction of software development overhead by reducing the distance between individuals and face-to-face communications, in global software development, the use of human power in various sites is considered. Despite their inherent differences, the combination of these two approaches has received considerable attention from researchers and software professionals. Meanwhile, the lack of a model or tool capable of assessing teams' adaptation to Agile methods seems to be a research gap. The current research aims to solve this challenge by proposing a model in this regard. Considering the major related factors and weighting them, this model allows software teams to assess the rate of their adaptation and success in global software development.&lt;/span&gt;
Combining solutions of the optimum satisfiability problem using evolutionary tunneling

The optimum satisfiability problem involves determining values for Boolean variables to satisfy a Boolean expression, while maximizing the sum of coefficients associated with the variables chosen to be true. Existing literature has identified a tabu search heuristic as the best method to deal with hard instances of the problem. This paper combines the tabu search with a simple evolutionary heuristic based on the idea of tunneling between local optima. When combining a set of solutions, variables with common values in all solutions are identified and fixed. The remaining free variables in the problem may be decomposed into several independent subproblems, so that parts of the solutions combined can be extracted and combined in an improved solution. This solution can be further improved by applying the tabu search in an improvement stage. The value of the new heuristic is demonstrated in extensive computational experiments on both existing and new test instances.