Reviewerly/exHarmony huggingface dataset:
Lossless and Reversible Data Hiding using Public Key Cryptography

In today’s world, the internet is a platform, where large amount of data can be obtained and transferred. Different technologies and internet access are used to transfer the data which can be accessed by authorized and unauthorized users.The major drawback of these technologies are that any unauthorized person can access it.Hence encryption and decryption is perform on Message/Data .In encryption the plain text/image is converted into cipher text/image.The technique of data hiding is used to hide the data that has to be transferred from the source to the destination.The process involves insertion of secret message in the cover image which is encrypted with the help of AES algorithm. This algorithm generates public/private key. All this process can be performed in lossless and reversible manner.
THE MAIN CHARACTER INNER CONFLICT ELEMENT IN DRAMA MANUSCRIPT NYANYIAN ANGSA CREATION BY ANTON CHEKOV AND THE IMPLICATIONS TOWARD LITERATURE TEACHING

Abstract: The inner conflict element which happen to main character in the drama script nyanyian angsa creation by Anton Chekov. The research method which using for analysis the script is qualitative method that description analysis. Research focus internal conflict element in drama script nyanyian angsa creation by Anton Chekov with subject focus element Id &gt;&lt; Ego, Id &gt;&lt; Eros and Superego &gt;&lt; Thanatos. The research instruments analyze scene that have an element of inner conflict in the script nyanyian angsa creation by Anton Chekov. To get the results the writer using presentation table from the element of inner conflict that accumulated. The impact of implications for students, the students must be directly involved actively in literary learning activities that is drama script in the school. The student also required to understand the contents of the drama script very well. To improve literature learning that is drama script, students must improve own learning method outside of school hours, for example be part of theatre extracurricular activities. This is intended so that the ability of students can be channel properly. Key words: inner conflict, drama script, literature teaching.
Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems

Deep Neural Networks (DNNs) with sparse input features have been widely used in recommender systems in industry. These models have large memory requirements and need a huge amount of training data. The large model size usually entails a cost, in the range of millions of dollars, for storage and communication with the inference services. In this paper, we propose a hybrid hashing method to combine frequency hashing and double hashing techniques for model size reduction, without compromising performance. We evaluate the proposed models on two product surfaces. In both cases, experiment results demonstrated that we can reduce the model size by around 90 % while keeping the performance on par with the original baselines.
Adaptive nonparametric estimation of a component density in a two-class mixture model

A two-class mixture model, where the density of one of the components is known, is considered. We address the issue of the nonparametric adaptive estimation of the unknown probability density of the second component. We propose a randomly weighted kernel estimator with a fully data-driven bandwidth selection method, in the spirit of the Goldenshluger and Lepski method. An oracle-type inequality for the pointwise quadratic risk is derived as well as convergence rates over Holder smoothness classes. The theoretical results are illustrated by numerical simulations.
SPIRITUAL-ENLIGHTENMENT AND LANGUAGE COMPATIBILITY

The sociality of science is manifested, first of all, in its humanity, in its service to the interests of human, in the facilitation of nature and society for man, that is, in the improvement or facilitation of the object of study. Until linguistics emerged as an independent science, it was part of the sciences of philosophy, and logic. When he broke away from them, he was surrounded by the natural sciences. This led to the view of language as a biological phenomenon, and linguistics as a science within the biological sciences. Although the science of linguistics gained its independence only in the 19th century and began to respond to the demands of the time within the framework of its own problems, it took on a social order and was engaged in its fulfillment in other disciplines. This can be verified on the basis of observation against the background of socio-political and cultural-enlightenment development. Key words: sociality of science, independent science, sciences of philosophy, and logic, socio-political and cultural-enlightenment development.
Design and technological requirements for the production of the TV Media reports by 360 technology

The television report is one of the important templates in the satellite channels, through the delivery of information, details of events and the impressions of specialists to the recipient in a professional manner according to the standards and traditions of television work, which is completely different from other news sources and other templates. Correspondents compete to find different ideas, each according to his point of view and the way in which the information arrives, and the details of the event, whatever the political, cultural, sports. Television journalism in general suffers from a significant lack of attention among viewers. On average it can not keep the viewer's attention for more than forty seconds. But the intense competition between satellite TV on the one hand and between state television on the other makes it difficult to keep the viewer tight in front of the television screen. In order to keep the viewer in front of the screen as long as possible. This will only be achieved by working to provide as much accurate and new information as possible in an attractive and simple template that the viewer accepts. Most television reports, or directed to social media platforms, were very ordinary, sometimes similar, containing the same images and angles. But the BBC produced 360-degree video stories that brought viewers to the center of the event without angles or photo selection. BBC was not the only one. The use of these technologies is an opportunity for interactive journalistic experiences different from those used by the public in the past.This research aims to identify the design and technological requirements and the most important cameras used to produce 360-degree media reports. From Wagih Search: Search adopted in the course on the descriptive approach and analysis Almstkhaddh methods for the production of media reports produced a 360-degree technology, access to how to keep pace, especially in the world of photography and Internet technology for technological development.
Enhancing Student Reading Skill through Strategy of Directed Reading Thinking Activity (DRTA)

This research examines the effect of the DRTA strategy as an effort in enhancing the students' reading comprehension skills in class V SD 41 Enrekang. A research methodology is a quantitative method for classroom action research. This review focuses on student learning outcomes and processes. The study was conducted at Enrekang 41 Elementary School, Enrekang, with the subject of the fifth-grade students of Enrekang 41 Elementary School, Enrekang, consists of 21 students. The CAR is carried out in four stages: planning, implementing actions, observing, and reflecting. From the implementation obtained data collected by learning outcomes tests. Then the data is analyzed and processed quantitatively. The results of the study showed that Directed Reading Thinking Activity (DRTA) in the first cycle is in the less category (K), and after the second cycle action is carried out, there is an improvement in students’ scores and has reached the specified indicators. From the result, the researcher concludes that the students' reading comprehension skills in Indonesian subjects in class V SD 41 Enrekang, Enrekang Regency has an improvement after applying of the strategy of Directed Reading Thinking Activity (DRTA).
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning

We consider the theoretical problem of designing an optimal adversarial attack on a decision system that maximally degrades the achievable performance of the system as measured by the mutual information between the degraded signal and the label of interest. This problem is motivated by the existence of adversarial examples for machine learning classifiers. By adopting an information theoretic perspective, we seek to identify conditions under which adversarial vulnerability is unavoidable i.e. even optimally designed classifiers will be vulnerable to small adversarial perturbations. We present derivations of the optimal adversarial attacks for discrete and continuous signals of interest, i.e., finding the optimal perturbation distributions to minimize the mutual information between the degraded signal and a signal following a continuous or discrete distribution. In addition, we show that it is much harder to achieve adversarial attacks for minimizing mutual information when multiple redundant copies of the input signal are available. This provides additional support to the recently proposed ``feature compression" hypothesis as an explanation for the adversarial vulnerability of deep learning classifiers. We also report on results from computational experiments to illustrate our theoretical results.
Research and Implementation of Violation Monitoring System for Electric Customer Service Hall

Automatic detection of violations will improve the efficiency of enterprise management and reduce the workload of employees. In this paper, an electric customer service hall monitoring system based on Improved Tiny-yolo v3 is developed for common violation in the services of electric customer hall: mobile phone playing behavior, smoking behavior, sleeping behavior, manicuring behavior and fighting behavior. The experimental results show that the system can meet the requirements of real-time and accuracy in electric customer service hall monitoring.
Prob2Vec: Mathematical Semantic Embedding for Problem Retrieval in Adaptive Tutoring

We propose a new application of embedding techniques for problem retrieval in adaptive tutoring. The objective is to retrieve problems whose mathematical concepts are similar. There are two challenges: First, like sentences, problems helpful to tutoring are never exactly the same in terms of the underlying concepts. Instead, good problems mix concepts in innovative ways, while still displaying continuity in their relationships. Second, it is difficult for humans to determine a similarity score that is consistent across a large enough training set. We propose a hierarchical problem embedding algorithm, called Prob2Vec, that consists of abstraction and embedding steps. Prob2Vec achieves 96.88\% accuracy on a problem similarity test, in contrast to 75\% from directly applying state-of-the-art sentence embedding methods. It is interesting that Prob2Vec is able to distinguish very fine-grained differences among problems, an ability humans need time and effort to acquire. In addition, the sub-problem of concept labeling with imbalanced training data set is interesting in its own right. It is a multi-label problem suffering from dimensionality explosion, which we propose ways to ameliorate. We propose the novel negative pre-training algorithm that dramatically reduces false negative and positive ratios for classification, using an imbalanced training data set.
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Special issue on deep learning for video text analysis

An exact algorithm for estimating the dynamic stochastic block model is proposed. This model assumes a hidden Markov chain for the evolution of the social behavior of a group of individuals at repeated time occasions and may be used to assign these individuals to the latent blocks in a dynamic fashion. For the estimation of this model, the proposed exact algorithm maximizes the target function introduced by Matias and Miele [7]. This function is derived from a variational approximation of the model log-likelihood, based on the assumption that the latent variables identifying the blocks are a posteriori independent across individuals, but not across time occasions. A simulation study is performed to compare the exact algorithm with the approximate maximization algorithm proposed by Matias and Miele [7]. Results show that there is a certain advantage of the first in terms of dynamic assignment of individuals to the latent blocks in comparison to the true blocking structure, as measured by the adjusted Rand index.
Information-Theoretic Approximation to Causal Models

Inferring the causal direction and causal effect between two discrete random variables X and Y from a finite sample is often a crucial problem and a challenging task. However, if we have access to observational and interventional data, it is possible to solve that task. If X is causing Y, then it does not matter if we observe an effect in Y by observing changes in X or by intervening actively on X. This invariance principle creates a link between observational and interventional distributions in a higher dimensional probability space. We embed distributions that originate from samples of X and Y into that higher dimensional space such that the embedded distribution is closest to the distributions that follow the invariance principle, with respect to the relative entropy. This allows us to calculate the best information-theoretic approximation for a given empirical distribution, that follows an assumed underlying causal model. We show that this information-theoretic approximation to causal models (IACM) can be done by solving a linear optimization problem. In particular, by approximating the empirical distribution to a monotonic causal model, we can calculate probabilities of causation. We can also use IACM for causal discovery problems in the bivariate, discrete case. However, experimental results on labeled synthetic data from additive noise models show that our causal discovery approach is lagging behind state-of-the-art approaches because the invariance principle encodes only a necessary condition for causal relations. Nevertheless, for synthetic multiplicative noise data and real-world data, our approach can compete in some cases with alternative methods.
Graphical approach to index and retrieve semi-standard young tableaux (SSYT) for a partition of n

Semi-Standard Young Tableaux includes many applications in combinatorics, group representations, invariant theory, symmetric functions, and the theory of algorithms. Out of the many combinatorial objects Semi-Standard Young Tableau (SSYT) is the one on k-symbols. This paper aims to present how to find hook lengths, formulae for evaluation of total number of standard and semi standard young tableaux.The Semi-Standard Young Tableaux are used to label the basis vectors of the standard or Young Yamanouchi basis of the symmetric group sn. This papergives a new graphical method to find ranking and unranking of the semi-standard Young tableau for a partition of degree n in sn. Graphical method of approach is explained forthe symmetric group s6 using a partition of degree 6 as an example.
서사적 자아(narrative self)의 교육철학적 함의 고찰

This study is conducted to examine the implications of educational philosophy and to provide new interpretation of human nature and awareness through ''narrative self'', rather than subjective and rational self, which the western traditional epistemology have focused.Alasdair MacIntyre, by the concept of narrative self, have emphasized on the new virtue, while criticizing the issue of modern society''s loss of virtue. The narrative self is the conscious that forms its identity within a unified narrative of one''s life form and seeks oneself within specific relationships of others and world.This thesis ultimately seeks to reveal that understanding oneself and others based on a multiple contexts of life and relationship with others is furthermore rational and that it is necessary to pursue the virtue by identifying one''s conscious and identity based on one''s distinct social, historical role and status within community.
Optimization of Data using Artificial Bee Colony Optimization with Map Reduce

We are developing an idea through this paper which would give any question the perfect and best answer. Existing system is not capable of classifying according to different patterns. This compromises with efficiency of the system and quality of final result. In this project Parallel Clustering optimization method is formed by amalgamation of Map-Reduce with Ant Bee Colony Optimization Technique for improving the efficiency and success of the data science method. In addition, related running services on a Hadoop network are predicted with the help of Map Reduce algorithm.
A Mobile Application Design to Prevent Criminal Acts in Lima, Peru

In the province of Lima, Peru, criminal acts are increasing every day; it is a social problem that affects many people, who often try with the life of the indignant person, becoming the greatest fear of the community.For this reason, a mobile application was designed that allows the inhabitants to report and share the criminal acts that occur in their environment in real time, allowing them to prevent such acts.This application was designed using the Balsamiq tool, which allows each sketch to be developed in an organized manner.The result was the development of each module that addresses each of the functionalities of the application design for its correct structuring with the Balsamiq tool.These results will help the inhabitants of Lima, Peru, to expose the facts of which they are victims, without the immediate need to go to the police station, and which will be proposed for development to different competition funds.
Penerapan Metode Fuzzy Mamdani untuk Menentukan Jumlah Pendapatan Pegadaian Berdasarkan Jumlah Omset Harga Emas dan Kurs

Corporate planning in determining the amount income decision making for the period based on turnover, gold and exchange rates at the Pegadaian Syariah Branch Subrantas Sidomulyo Unit Pekanbaru. The Purpose of this study is to investigate the use of fuzzy logic aplication using Mamdani methos for dicision making determination of total income. The results of this study indicate that the prediction of income with accuracy reaches 87,4632%.
Proposing to Use Artificial Neural Networks for NoSQL Attack Detection

Relationships databases have enjoyed a certain boom in software worlds until now. These days, with the rise of modern applications, unstructured data production, traditional databases do not completely meet the needs of all systems. Regarding these issues, NOSQL databases have been developed and are a good alternative. But security aspects stay behind. Injection attacks are the most serious class of web attacks that are not taken seriously in NoSQL. This paper presents a Neural Network model approach for NoSQL injection. This method attempts to use the best and most effective features to identify an injection. The features used are divided into two categories, the first one based on the content of the request, and the second one independent of the request meta parameters. In order to detect attack payloads features, we work on character level analysis to obtain malicious rate of user inputs. The results demonstrate that our model has detected more attack payloads compare with models that work black list approach in keyword level.
Augmented Reality based Navigation and Recognition System

The current navigation system requires the user to continuously map with the navigation application with the real-world environment. It sometimes leads to an incorrect path due to minor difference in the distance between different paths. The identification of nearby places of unknown locality is difficult as one has to ask for information and reviews which can be misleading. Recognition of unknown people for their authenticity cannot be guaranteed as one has to rely on official documents which can be fake. This paper aims to describe the design of an application that will provide the same reality-based environment as that seen through the naked eye, but it adds visual simulation or content to provide an enhanced view to the user during navigation. We will be using Augmented reality to provide users with more information, computer-assisted decision making, and interactive learning and training. The application will combine Google’s existing Maps data with a live feed from your phone’s camera to overlay walking directions on top of the real world and help you figure out which way you need to go. Identification of near-by places and authenticity of the unknown people can be done from the data stored on the cloud and will be augmented when scanned through the camera of the phone which is the only requirement of the application. It also enables the users to navigate indoors with the help of a radar map and arrow pointing towards the points of interest. This application enables the user to navigate using the mobile phone and get the directions augmented in the real world to take accurate decisions. The user can also navigate to different points of interest- indoor as well as outdoor. It also enables the recognition of places, as well as people and the details related to the same, get augmented.
Introspective Robot Perception using Smoothed Predictions from Bayesian Neural Networks

This work focuses on improving uncertainty estimation in the field of object classification from RGB images and demonstrates its benefits in two robotic applications. We employ a (BNN), and evaluate two practical inference techniques to obtain better uncertainty estimates, namely Concrete Dropout (CDP) and Kronecker-factored Laplace Approximation (LAP). We show a performance increase using more reliable uncertainty estimates as unary potentials within a Conditional Random Field (CRF), which is able to incorporate contextual information as well. Furthermore, the obtained uncertainties are exploited to achieve domain adaptation in a semi-supervised manner, which requires less manual efforts in annotating data. We evaluate our approach on two public benchmark datasets that are relevant for robot perception tasks.