Reviewerly/exHarmony huggingface dataset:
ROBUST DISCRIMINATIVE REPRESENTATION LEARNING VIA GRADIENT RESCALING: AN EMPHASIS REGULARISATION PERSPECTIVE

Real-world large-scale datasets usually contain noisy labels and are imbalanced. Therefore, we propose derivative manipulation (DM), a novel and general example weighting approach for training robust deep models under these adverse conditions. DM has two main merits. First, loss function and example weighting are common techniques in the literature. DM reveals their connection (a loss function does example weighting) and is a replacement of both. Second, despite that a loss defines an example weighting scheme by its derivative, in the loss design, we need to consider whether it is differentiable. Instead, DM is more flexible by directly modifying the derivative so that a loss can be a non-elementary format too. Technically, DM defines an emphasis density function by a derivative magnitude function. DM is generic in that diverse weighting schemes can be derived. Extensive experiments on both vision and language tasks prove DM's effectiveness.
Flash Multimedia Application: An E Learning Arabic Language for Mastering Fluency in Reading the Qur'an

Arabic language is one of the 6 international languages recognized by the united nations, as a muslim except learning English we must learn Arabic language. Arabic language is the main language to read the Qur'an and good Arabic language will be minimize errors when reading the Qur'an that can cause different meanings, basic Arabic learning made using Adobe Flash CS6 shows many examples of words in Arabic and there are also exercises to test the knowledge of Arabic language that has been learned by the user, is expected with this multimedia application allows users to learn Arabic.
Dual Discriminator Generative Adversarial Network for Single Image Super-Resolution

Single image super-resolution(SISR) is to reconstruct a high resolution(HR) image from a single low resolution(LR) image. In this paper, with generative adversarial networks(GAN) model as the basic component, we build a dual discriminator super-resolution reconstruction network(DDSRRN) to improve the quality of image super-resolution reconstruction. By adding another discriminator based on GAN, we combine the Kullback-Leibler(KL) with reverse KL divergence to make a unified objective function to train the two discriminators, and by using the complementary statistical characteristics of these two divergences, the prediction density is effectively dispersed in multi-mode, which can avoid collapse of the network model during the reconstruction process and improve the stability of model training. We build the content loss function using the Charbonnier loss and use the intermediate features information of the two discriminators to build the perceptual loss function and style loss function. The experimental results show that the proposed method has sharp edges and rich details in subjective vision, and obtains better subjective visual evaluation and objective quantitative evaluation.
援곗궛??숆탳 援먭낵紐⑹쓽 留뚯”???ㅻЦ 議곗궗 遺꾩꽍

Education on university writing began with early Korean writing and now it has varied from ?쁳op-level writing??to ?쁶riting for foreigners.??However,...
Exploraciones en la formación de competencias del docente de Licenciatura en Humanidades y Lengua Castellana frente a la incorporación de las tecnologías digitales

The present research is an exploratory and descriptive work of the training of the Bachelor of Humanities and Spanish Language students of the Pontificia Universidad Javeriana and the teachers already graduated and in exercise of the mentioned career in front of the incorporation of digital technologies in the practice of pedagogical work. It applies a mixed methodology of qualitative and quantitative approach that specifically identifies the strengths, weaknesses and perceptions that each of these investigated subjects have, so that it is possible to analyze and evaluate the teaching and learning contents in TIC that are developed today in the classroom.
Design of Knowledge-Base Teaching Activities for Earlier Diagnosis of Health Problem

In the health area, determine the earlier diagnosis of health problems is through the procedures of inspection specified, but sometimes the knowledge and experience that occurs from expertise in resolving a problem can be an added value in diagnosing patients. The procedures that an expert did is a teaching activity that a medical rookie doctor will learn. By not eliminating the position of an expert and the importance of the knowledge with experiences, it can be built a documentation place and digital storage. The experiences and knowledge that can be saved into a database called a Knowledge-Base which can be reused in determining for teaching activities the early diagnosis of health problems with a similar case besides a procedure. The first step is to design a model of development. By doing a literature review of previous studies, this research goal is to propose a model of the Knowledge-Base.
Modeling of Indonesia Composite Index using Artificial Neural Network and Multivariate Adaptive Regression Spline

The Indonesian Composite Stock Price Index is an indicator of changes in stock prices are a guide for investors to invest in reducing risk. Fluctuations in stock data tend to violate the assumptions of normality, homoscedasticity, autocorrelation, and multicollinearity. This problem can be overcome by modelling the Composite Stock Price Index uses an artificial neural network (ANN) and multivariate adaptive regression spline (MARS). In this study, the time-series data from the Composite Stock Price Index starting in April 2003 to March 2018 with its predictor variables are crude oil prices, interest rates, inflation, exchange rates, gold prices, Down Jones, and Nikkei 225. Based on the coefficient of determination, the determination coefficient of ANN is 0.98925, and the MARS determination coefficient is 0.99427. While based on the MAPE value, MAPE value of ANN was obtained, namely 6.16383 and MAPE value of MARS, which was 4.51372. This means that the ANN method and the good MARS method are used to forecast the value of the Indonesian Composite Stock Index in the future, but the MARS method shows the accuracy of the model is slightly better than ANN.
INTERVISTA A STEFANO PONTIGGIA

Cyberspace is only one of the many metaphors used to describe the Internet.While there is a growing body of literature on the identity formation in cyberspace, there are important gaps in this field.One of these is related to the analysis of the use of digital technologies by the Northern Canadian Indigenous people.Precisely, the author, focusing her attention on Tåîchô and Yellowknives Dene communities in Northwest Territories of Canada, analyzes the contents of their web-sites and online archives in order to understand how these native groups promote their culture and spread out their knowledge through digital technologies for working toward decolonization.
ФАКТОРЫ, ОБУСЛОВИВШИЕ ГУМАНИСТИЧЕСКУЮ НАПРАВЛЕННОСТЬ ПЕДАГОГИЧЕСКОГО ТВОРЧЕСТВА ДЖ.П. НАЙКА

It is considered the definition of the basic prerequisites and factors that contributed to the formation of the pedagogical views of the great Indian teacher of the XXth century, J.P. Naik. The study period covers the time from the birth of a great teacher to the beginning of his professional work activity. The main reasons and prerequisites for the formation of the humanistic orientation of the pedagogical activity of J.P. Naik were connected and determined, first of all, by the state and influence of the external environment, i.e. the socio-economic and geopolitical position of India, which had a direct impact on the processes, events, ideology, mentality of the population, determined the nature and content of the behavior of the Indians. Since childhood, observing the harsh living conditions of the Indian people, as well as analyzing the country's political and socio-economic situation, J.P. Naik concluded that the country's independence can be achieved not by armed means, but by peaceful means. Influenced by the ideas of M.K. Gandhi on the importance of education for the development of the country, he realized that education is a leadingfactor in social progress, a means of increasing the material and moral level of the population, realizing personal needs and interests, and this can be achieved by increasing the educational level of the poor, reviving the national school, raising young people in the best traditions of Indian culture
Latent Representation of Tasks for Faster Learning in Reinforcement Learning

Reinforcement learning (RL) is an field of machine learning (ML) which attempts to approach learning in an manner inspired by the human way of learning through rewards and penalties. As with other ...
A New Expert Hepatitis Diagnosis System Based on Linear Discriminant Analysis - Extreme Learning Machine Classifier

In this study, a new expert hepatitis diagnostic system based on the Linear Discriminant Analysis (LDA) -Extreme Learning Machine (ELM) Classifier method is suggested. ELM has various applications in fields such as biomedical engineering, computer vision, system identification and robotics. In this paper, a detailed explanation of the ELM development is provided. The UCI machine learning database was used for the hepatitis illness dataset. Proposed method performance is evaluated through statistical methods such as classification accuracy, sensitivity and specificity statistical analysis methods. The structure of this hepatitis diagnosis system can be described in three phases. In first phase, the hepatitis dataset is obtained and features reduced. These 19 features of the hepatitis dataset are reduced to 10 features using Linear Discriminant Analysis (LDA), Principle Component Analysis (PCA) and Generalize Discriminant Analysis (GDA) methods respectively. In the second phase or classification stage, each analysis reduced feature set is given to the Extreme Learning Machine (ELM) classifier. This phase indicated that the Linear Discriminant Analysis (LDA) - Extreme Learning Machine (ELM) Classifier method outperformed the two other methods, PCA-ELM and GDA-ELM. Finally, in third phase, the diagnosis performance of our LDA-ELM expert system for diagnosis of hepatitis is calculated. The resulting classification accuracy of this system was 95.17 %. In this study, results are compared to hepatitis diagnostic approach studies using the same or like dataset and conclude that the high classification accuracies.
METODE TRANSFORMASI PENGETAHUAN TERHADAP PENINGKATAN KOMPETENSI (PELATIHAN KOMPUTER) SMP, SMA, DAN UMUM DI DESA BUKIT LANGKAP KEC. KARANG JAYA KAB.MUSI RAWAS UTARA

The impact of the expandingeconomy cause the decrease community incomesespecially the income of farmer income, from the price of rubber, palm oil, crops which were getting lower in price. The growing need for life requires the community to be able to fulfill their daily needs even with minimum fulfillment. Our concern for the future generation of children  will inspire us to conduct direct observations of people in Bukit Langkap village kec Karang Jaya Kab. Musi Jaya Kab. Rawas Utara. The goal is to produce Knowledge Transformation Method is by training approach to improve children  competency in junior high schooland general education in Bukit Langkap Village. Identifyingthe needs sueh asthe edulpment which use in training we get it by rent. The main target is senior and junior high sehool students the study principle by direct seminars with a practical approcch from the training result will be done a produce knowledge transform method by trahing /practice approach in using computer comprehension such as hase introduce of computer, can programe the word, exsel, and powerpoin, and we hope will estabiish the  sustainability relationship even thoug the research has beeb completed.
Cascade Feature Pyramid Neural Nwtwork for Object Detector

Early object detection networks apply single scale feature to predict the classification and regression. However, the semantic information which is from the low-level features is less than that on the high-level features, and locations of objects on the low-level are more accurate than that on the high-level. Recently, feature pyramid fusion is widely applied by one-stage object detectors (e.g. DSSD, RefineDet), which achieves encouraging results of the object detection, but only simply constructs the feature pyramid according to multi-scale feature maps. In our work, we design a network, called CFPNet, which applies cascade feature pyramid layer (CFP) to predict the classification and regression. CFPNet achieves 80.1% mAP with small input size (320× 320) and 82.0% mAP with large input size (512 × 512), experimenting on PASCAL VOC2007 and PASCAL VOC2012. The network with low dimension input size runs 34 FPS in NVIDIA 1080Ti, which achieves the high accuracy and maintains fast speed.
The Effect of Logistics Service Quality on Customer Satisfaction and Repurchase Intention of Foreign-owned Shopping Malls in China

Purpose - The study examined the impact of logistics service quality of foreign-owned shopping malls on customer satisfaction and repurchase intention in China as well as attempted to explore the mediated effect of customer satisfaction on the relationship between logistics service quality and repurchase intention. Design/methodology/approach - To test the hypothesis intention relative to foreign-owned shopping malls. Empirical analysis was performed on the collected data using an SPSS statistical package. Findings - First, except for the return service quality, the three logistics service quality sub-factors of China’s foreign-owned shopping malls have a positive effect on customer satisfaction and repurchase intention. Second, except for the return service quality, the mediating effect of customer satisfaction on the relationship between logistics service quality and repurchase intention was significant and found to be a partial mediator. Research implications or Originality - The scale of Chinese consumers’ direct overseas purchases have been expanding, and the problems facing China’s foreign-owned shopping malls are almost related to logistics services. However, the academic research on the impact of logistics service quality of foreign-owned shopping malls especially on Chinese consumer satisfaction and repurchase intention is not sufficient.
IMPLEMENTASI METODE NAÏVE BAYES CLASSIFIER UNTUK IDENTIFIKASI JENIS JAMUR

Being in a country that has abundant natural resources and biodiversity, of course, something that should be grateful for, such as its diversity of flora. The climate is very suitable for growing various types of plants. One of them is the food sector, especially horticulture, a horticultural commodity that is often found and widely used consumption materials by the community are mushrooms. The types of fungi of the genus Agaricus and Lepiota are often found around the community. There are types of mushrooms that are edible and some are poisonous. The type of fungi genus agaricus and lepiota which have poisons can cause pain in people who consume them, can even have an impact on death. To distinguish between mushrooms that are safe for consumption and those that are poisonous is very difficult. Therefore the need for problem solving to contribute to identifying the fungi is safe to eat or toxic. In this study the researcher tried to contribute in solving the problem in order to identify fungi using the naive bayes classifier method. Naive bayes classifier will classify the fungi dataset of genus agaricus and lepiota using probability calculations. In the scheme the testing data will be inputted with certain attributes, with subsequent training data with the NBC method testing data will be classified with training data so that the results of the testing data are included in the edible or poisonous category. The data used in this study is a collection of mushroom data (genus agaricus and genus lepiota), this dataset is taken from the UCI Machine learning repository. The mushroom data has 23 attributes based on morphological characteristics, with a total of 8124 mushroom records. The mushroom data has 23 attributes based on morphological characteristics, with a total of 8124 mushroom records. After using the 10-fold cross validation scheme, the average method of naive bayes method in the history of agaricus and lepiota mushrooms was found to be an accuracy value of 86.64 using the method of good classification.
Blasphemy and the European Court of Human Rights: A Small Step Forward, A Giant Leap Back

This contribution compares and contrasts recent jurisprudential approaches to religiously offensive speech acts, comparing and contrasting especially the cases of E.S. v Austria and the ‘Pussy Riot’ case.
Assessment of Soil pH and Electrical Conductivity Dynamics from the Use of an Innovative Bio-remediating Agent on a Certain Strongly Acidic Soil of Niger Delta

This study is a preliminary investigation on the bioremediation and restoration of a degraded and strongly acidic soil in Okpoma, Bayelsa, Niger Delta Region of Nigeria, using a scientifically formulated, innovative and potentially commercializable technical grade bioremediation product (LaSegad-6531), whose basic chemical characteristics are provided. Formulation was applied at rates 0 %, 33 %, 50 % and 67 % (v/v) using a well-developed standard operating procedure (SOP) under controlled environmental conditions of screen house. Impact on soil pH, electrical conductivity (EC) and crop growth performance was assessed.  A regression model was developed to assist on the choice of applied rate for a desired soil EC to avoid soil sodicity condition.  Results showed that LaSegad-6531 ameliorated soil acidity by raising soil pH and EC to acceptable ranges and improved indicator crop (Pineapple: Ananas comosus ) growth relative to control systems. In terms of crop growth, product efficiency increased as: Rate 0 % < Rate 67 % < Rate 50 % < Rate 33 %. Study points to user friendly SOP, product efficacy, cost effectiveness and suitability in the difficult terrain of the Niger Delta region of Nigeria.  In addition, the product is designed to be packaged in various customized weight or volume capacities. Further studies on near field conditions (pilot trial and field – scale trials) are ongoing Keywords : Environment, Niger Delta, Nigeria, Soil acidity, Petroleum activities,  Remediation
Object-based Image Discrimination Relationship Recognition

With the development of self-media, we can publish images freely on the Internet, and there will be some discriminatory images more or less. Discrimination is an emotional relationship. However, there is no open data set to help us complete the task of discriminatory image detection. In this article, we created a simple data set that can be used to detect discriminatory relationships. Then, on this data set, we propose a baseline for discriminatory relationship detection. This baseline is a multi-task network based on translation embedding model, which can output both the action categories of objects in the graph and the relationship categories between the two. Experiments show that our multi-task network can effectively detect relationships, and it is better than the simple translation embedding model.
IMPLEMENTASI ALGORITMA APRIORI DAN FORECASTING PADA TRANSAKSI PENJUALAN

One of the most important parts of a retail business or product distribution company is inventory management. Transactions with very large amounts in a certain period make the transaction data on sales, prices, and availability of goods must be managed properly. This study was delivered to facilitate the company in determining policies related to sales and availability of goods through the purchase pattern of association rules and sales predictions using the Moving Average method. Association rule is data mining techniques contained in the Apriori algorithm. This algorithm is able to shows random relationships in a number of transactions. The test resulted in three patterns of purchasing goods with the highest frequency namely Milo Activ-go UHT Cmbk 36x115ml, Bear Brand RTD Milk 30x189ml and Milo Activ-Go UHT Cmbk 36x190ml with values of 46.17%, 41.97% and 15.39%. The Moving Average result, sales predictions produce a total of 3669, 3280, and 2619 for each item that can be prepared in the next period. This can be a company's reference in predicting goods that are in demand or not, determine the number of sales and prioritize the procurement of goods based on the rules of the association produced.
PENGARUH RANAH AFEKTIF DAN KECERDASAN EMOSIONAL TERHADAP PRESTASI BELAJAR SISWA PADA MATA PELAJARAN EKONOMI KELAS XI IPS DI SMA NEGERI 8 KOTA JAMBI

Abstract This study aims to determine the effect of the affective domain and emotional intelligence partially and simultaneously on student achievement in class XI IPS SMA Negeri 8 Jambi City. In this study, the authors used descriptive and verification research methods. The number of samples from both classes was 119 students. Based on the results of the study show that, (1) Affective Domain (X1) of 2,382 and t table of 1,987 from the comparison results, it can be seen that tcount is greater than ttable (tcount> ttable). Then H0 is rejected and Ha is accepted, meaning that there is an influence on the Affective Domain (X1) on Learning Achievement (Y) in Economics subjects in class XI IPS SMA Negeri 8 Jambi City. (2) Emotional Intelligence (X2) of 3,535 and ttable of 1,987, from the comparison results it can be seen that tcount is greater than ttable (tcount> ttable). Then H0 is rejected and Ha is accepted, meaning that there is an effect on Emotional Intelligence (X2) on Learning Achievement (Y) in economics class XI IPS at SMA Negeri 8 Jambi City. (3) From the research results it can be seen that the Fcount is 3,586 by comparing the Fcount with Ftable, with a significant level α = 0.05 (5%). It can be seen that the Fcount is 9,377 by comparing the F table α = 0.05 with the numerator free degree 2 and the denominator free degree 89, the F table is 3.04. Fcount greater than Ftable (9,377> 3.04) means that it can be said that there is an influence between Rana Afekti and Emotional Intelligence together (simultaneously) on Learning Achievement in Economic subjects in class XI IPS of SMA Negeri 8 Jambi City. Keywords : Ranah Afektif , Kecerdasan Emosional, Prestasi Belajar
Optimal Computation Resource Allocation in Vehicular Edge Computing

Vehicular edge computing is proposed as a new promising paradigm that provides cloud computation capabilities in close proximity to vehicles, which can augment the capabilities of vehicles. In this paper, we study the problem of computation resource allocation of edge servers for a vehicular edge computing system. We consider the constraint of limited computation resource of edge servers and vehicles can decide that vehicular applications are locally executed or offloaded to edge servers for execution to minimize the completion time of applications. We model the problem as a Stackelberg game and then prove the existence of Nash equilibrium of the game. Furthermore, we propose an algorithm to compute the Nash equilibrium effectively. Numerical simulation results demonstrate that our proposed algorithm can greatly reduce the average completion time for all applications and outperform the benchmark approaches.
Virtual Calibration Pattern Realization for Hybrid-FOV Multiview Calibration*

Multiview vision systems are commonly applied in different fields at present, including hybrid-field-of-view(hybrid-FOV) multiview systems. The difference between cameras’ FOVs results in the difficulty of calibration, such as lack of information for cameras with small FOVs. All the information acquired by the other cameras and the projective geometry between them should be utilized in camera calibration. In this paper, a method of generating redundant constraints with trifocal tensor and the information from the cameras with a large FOV is proposed. The process is described after some reminders of trilinearities. Then, two simulated experiments based on this method have been implemented. The results and analysis show the feasibility of this method.