Reviewerly/exHarmony huggingface dataset:
ABOUT UNDERSTANDING OF THE OFFICIAL DOCUMENT ACCORDING TO THE ARTICLES 292 AND 327 OF THE CRIMINAL CODE OF THE RUSSIAN FEDERATION FOR THE PURPOSE OF QUALIFYING CRIMES

The article identifies and reveals the Corpus delicti of forgery (Article 292 of the Criminal Code) and the manufacture of counterfeit documents (Article 327 of the Criminal Code). The article concludes that there is a differentiated understanding of the official document for the composition of crimes from different chapters of the Criminal Code of the Russian Federation. The article concludes that there is a differentiated understanding of the official document for the crimes from different chapters of the Criminal Code of the Russian Federation. The legal content of the subject of the crime is determined by the specifics of protected public relations that are damaged, as well as other signs of the crime. It is necessary to update the understanding of forged documents in connection with the introduction of official electronic documents and private documents. It is concluded that for the purposes of proper qualification of crimes, the signs of the subject of official forgery (Article 292 of the Criminal Code) and the production of forged documents (Article 327 of the Criminal Code) should be fixed in the notes to the relevant articles of the Criminal Code, taking into account the specifics of the specific object of crimes.
An Open-Source Area-Optimized ECEG Cryptosystem in Hardware

Hardware implementations of advanced cryptographic schemes gain importance for emerging cyber-physical and autonomous systems and with that the need for area-optimized hardware is also increasing. In this paper, we present a scalable, area-optimized elliptic curve ElGamal cryptosystem module that integrates both the encryption and decryption operations into a single block. With the help of the Universal Elliptic Curve Arithmetic unit, that is designed to perform elliptic curve point multiplication, doubling and addition, the area has been kept to a minimum to fit on the Xilinx Spartan-6 LX75 FPGA. The design supports the NIST-recommended curves over prime fields.
A Further Step Towards Automatic Domain Modelling by Relevant Information Extraction

A still unsolved issue in human activity recognition, as it is being used in many smart systems, is the availability of labeled training data or, in other words, information about what sensors actually are recording. A possible solution to this problem is to build detailed semantic domain models specifying, in different detail, complex compound activities. Such models would allow retrieving the required information without the necessity of time-consuming labeling. On our way to develop a method to leverage text-based domain descriptions automatically to build such domain models, we previously introduced a method to extract domain-relevant information from texts. However, this method still included the requirement to hand-craft socalled “regular expressions,” which have to be adjusted or rebuilt for different languages and different styles. Even though only done once for a language or style, the necessity of handcrafting regular expressions (and their fine-tuning by experts) still requires extensive work. In this paper, we present the next step to automatize information extraction by substituting the regular expressions with an automated neural network. All steps in this method are now fully automatic and do not require any hand-crafting. The performance of this new method is equal to the performance of the regular expressions method before (70 % precision and recall).
Post-Quantum Blockchain for a Scalable Smart City

Smart Cities enclose various industries, sectors, and components. A Smart City application benefits from the data collected using a tremendous number of sensors serving to establish an accurate corporative decision. However, the communication between different components and application of a Smart City exhort security measures as it faces critical security attacks and integrity issues. To medicate this dilemma, researches have used the assistant of Blockchain to secure Smart Cities and improve its decision’s accuracy. Yet, with the recent development of Quantum Computers, Quantum-based algorithms are certainly menacing the security of classical encryption together with Blockchain itself. Thus, threaten the insurance of Blockchain-based application including critical applications such as Smart Cities. In this paper, we demonstrate the Blockchain-based Smart Cities’ framework and we present an understanding overview that encloses the menaces of a Quantum computer on Blockchain and Blockchain-based applications essentially Smart City. We explain as well some Post-Quantum solutions concerning the security of Blockchain-based Smart City.
ORE CLASSIFICATION OF PSEUDOBRECCIA ORE IN THE 144 ZONE GOLD DEPOSIT: A CHEMICAL REPLACEMENT MODEL, BARE MOUNTAIN RANGE, NEVADA

Abstract The 144 zone is a pseudobreccia-hosted, disseminated gold deposit that formed in the middle to late Cambrian Bonanza King dolostone along an unconformity with the underlying early to middle Cambrian Carrara limestone at Bare Mountain, southern Nevada. Underground mapping revealed spatial relationships between breccia types, host rocks, and alteration assemblages that are related to gold mineralization. Samples were collected along transects from low- to high-grade Au and were analyzed using petrography, applied reflectance spectroscopy, scanning electron microscopy, and electron probe microanalysis to characterize mineral assemblages and evaluate gold deportment. Two breccia types are identified. Breccia type 1 clasts consist of dolomite, dolomite with phengite, and quartz cemented in a quartz-rich matrix. Breccia type 2 has similar clasts of dolomite, dolomite with phengite, and quartz, but the matrix is phengite dominant. Neither breccia type has a preferred association with gold, which occurs with goethite that replaced pyrite in both breccias. Clast and matrix compositions and textures show that the two breccia types formed at the same time by selective dissolution and replacement of the lowermost Bonanza King dolomite. Fluid-rock reaction transformed massive dolomite into pseudobreccia. Quartz replacement of dolomite plus the precipitation of pyrite, Au, and phengite yielded the 144 zone pseudobreccia matrix. The geology that characterizes gold mineralization in the 144 zone can be applied to exploration throughout Bare Mountain. Other localities where the same stratigraphic contact is cut by silicic dikes of similar age provide drill targets in the mining district.
Spatial Transformer Steerable Nets for Rotation and Flip Invariant Classification

The paper focuses on problem of achieving approximate rotation and flip invariance of CNNs for classification. Group equivariant and steerable convolutional nets are models that could generate rotation and flip equivariant representations of input images. However, training and evaluation of such networks requires much memory and computations. We propose to use small steerable network to obtain orientation vector that is equivariant to rotations and use it to compute rotation invariant tensor, and feed it to usual CNN. We show that in case there is only one object on the scene our model shows approximate rotational and flip invariance and works faster than aforementioned approaches.
Detailed Study on the Features of Mobile Applications

Today, almost everyone has a smartphone and considering the widespread use of smartphones, the importance of mobile applications is clear. The use of smartphone technologies in mobile applications also provides new possibilities and better performance. Therefore, in this article, the aim is to provide a review investigation of the importance and efficiency of mobile applications and their technical aspects like search features, social media networking, responsive mobile app designs, less keyboard and more touch, getting feedback and working offline.
Disk Failure Prediction: An In-Depth Comparison Between Deep Neural Networks and Tree-Based Models

Disk failures are a constant challenge for data centers, which could lead to data loss or even financial losses. Recently, researchers have proposed predictive models based on SMART attributes. However, most previous studies were often conducted with small-scaled data and usually aimed to predict disk failures just a few hours in advance. This paper aimed at predict if a disk will fail within the next 30 days based on a large scale real world data. The dataset used was from the PAKDD 2020 Alibaba AI Ops Competition, which contains real-world logs from around 170 thousand disks during July 2017 to July 2018. We investigated 3 different kinds of solutions in depth for this task, including time-series prediction, anomaly detection and binary classification. We studied the reasons behind the differences in performance among models, and we proposed a series of data processing methods based on our elaborate feature analysis in order to predict disk failures. Both the offline validation and online testing showed that our observation and proposed methods are promising.
A Fast Algorithm for the Largest Area First Parsing of Real Strings

The largest area first parsing of a string often leads to the best results in grammar compression for a variety of input data. However, the fastest existing algorithm has Θ(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> log N) time complexity, which makes it impractical for real-life applications. We present a new largest area first parsing method that has O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) complexity in the improbable worst case but works in the quasilinear time for most practical purposes. This result is based on the fact that in the real data, the sum of all depths of an LCP-interval tree, over all of the positions in a suffix array of an input string, is only larger than the size of the input by a small factor α. We present the analysis of the algorithm in terms of α, and the experimental results confirm that our method is practical even for genome sized inputs. We provide the C++11 code for the implementation of our method. Additionally, we show that by a combination of the previous and new algorithms, the worst-case complexity of the largest area first parsing is improved by a factor of <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> √N.
Applying Weighted Finite State Transducers and Ripple Down Rules for Myanmar Name Romanization

Romanization known as Latinization that refers to the representation of names with Roman (Latin) alphabets. The Romanization process is not trivial especially for Myanmar Language (Burmese) due to different Roman variations of a single Myanmar proper noun. The Myanmar Name Romanization project has so far developed a 55K Romanized word pairs of Myanmar personal names. We apply Weighted Finite State Transducers (WFST) and Ripple Down Rules (RDR) based tagging approaches to the task of Myanmar name Romanization and vice versa. We perform experiments on one closed test data set (5,000 of training data) and three open test data sets: 5,000 Myanmar personal names, 571 city and town names of Myanmar, and 292 Myanmar food names. The result shows that RDR approach gives better performance than WFST for open test data sets.
Effects of Training Difficulties on Reinforcement Learning Based Outdoor Robot Navigation System

This paper presents a map-based navigation system for outdoor mobile robots and results from different training difficulties on reinforcement learning implementations. The proposed navigation system can navigate the robots using maps in the form of 2D binary images. Navigation maps can be processed from conventional map services such as Google Map. The navigation system includes the path planning segment and the navigation segment. A-star search algorithm is used to plan paths on the map. Q-learning is applied in the navigation segment to train the robot to follow planned paths on the map. Location differences between the robot and the A-star generated path are used as states for q-learning. Experiments include navigation tests of two robots which are trained under different training difficulties. Success rate of reaching the goals is used to evaluate the navigation system. Simulation results display better navigation performances of the robot trained in the training settings with more difficulties.
Escaping the prison of style

We seek support for our notion of authorially open programming practices through a critical reading of the notion of "style" in our dominant programming cultures. We argue that this popular notion of programming style is inescapably infused with values which diverge from those of its supposed analogues in areas such as literary and artistic expression. By examining the discourse around and technical distinctions between programming styles, we reveal their fundamentally different nature in structuring dialogues between the writers of computational artefacts and those who experience them. Programming styles are predominantly discussed in inward-facing terms, i.e. with regard only to the experience of programmers with privileged access to the source code. Regardless of their chosen style, programs consist of "imprisoned expressions", built of design elements cut off from access to the program which executes in the world. We construct a miniature integration language, still bounded within the space of existing programming language styles, to solve an open authorship problem, and observe that the increased open ownership of expressions has come at a significant usability cost. We fail to escape the prison, and reflect that our own dialogue remains predominantly inward-facing, due to the lack of proper materials and vocabulary to put communities into correspondence. We look forward to more convivial venues and idioms for expressing computational artefacts, with more equal relationships between the ecologies of construction and ecologies of use.
Mythological Conceptualization in A.O. Balabanov’s Films and Interpretation of “The River”

This paper attempts to uncover the semantic message of “The River”, an unreleased film that was supposed to be a new program product in the filmwork of Aleksei Oktyabrinovich Balabanov. At the beginning of the article, the author reveals the director’s method of conceptualizing his films that appeal to the mythological conceptualization of the narrative structure in addition to the plot and genre of the film. The latter is clarified in the process of comparing the films with the structure of a fairy tale, which has also already been noted by some researchers of Balabanov’s movies. The novelty of the article is connected with a philosophical analysis of the indicated conceptualization of “The River” film-project (2002) and an attempt to identify aesthetic effects and symbolic meanings encoded in the film production. The author believes that the close attention of “The River” project’s director to the cultures of traditional society, and especially the culture of northerners — the Tofalars (Tofa), the Yakuts (Sakha), is due to the proximity of the traditional cultures of the North and the Arctic to the mythological method of conception in culture. In this sense, “The River” project was, in all likelihood, to become the director’s experiment in building an archaic topos with a crystalline mythological concept of the abundance of the natural over the cultural and the corresponding mentality and psychology of the actions of the “old era”. The main thing in this cinematic experiment was to take the culture “off the table” and analyze the natural spontaneity in human nature, with the subsequent “splitting” of mythological consciousness, breaking the epic circle of tradition with a symbolic outcome, through the concept of “boat” and “river”, to a universal human principle, metaphysical topos of thought. The prophetic gift of the director, embodied in a number of his films, is interpreted on the example of “The River” and reflects the message for the path of self-development of the cultures of Russian peoples.
Human Movement Analysis from the Egocentric Camera View

In this study, a method of human movement analysis is introduced according to making and utilizing human motion datasets in a first-person egocentric viewpoint using head-mounted cameras. Two steps of virtual and real tests are required to build the dataset. The blender has been used to capture the actions in the virtual mode with five thousand frames from various movements in different scenes to assure the reliability of the algorithm. Furthermore in real test 170000 frames captured in different actions from seventeen people. To recognize each act, the long short term memory architecture was utilized for the classification of the training database. In the process of this stage, the optical flow is utilized for obtaining the head and the concordance camera position, combined with the scene which is utilized for recognizing the motion pattern for each person.
An Enhanced Convolution Neural Network Based Approach for Classification of Sentiments

Sentiment analysis is an approach to analyse the opinion and views of the people from the text or images posted by them on social media like Facebook and Twitter. Sentiment analysis is a challenging task because it is not easy to analyse the exact views, opinions, and feelings of the text. The way of expressing feelings varies with people in different contexts and topics. This issue can be resolved by combining the text and prior knowledge. This research work proposes a deep convolutional neural network that uses the character to sentence-level information to perform sentiment analysis of tweets. A new approach for the initialization of the weights of the convolutional neural network is suggested which helps to train the network efficiently and helps to find effective features. The model is further tuned by a deep learning model which reduces the classification error. It uses word vector features with feature engineering by means of a convolution neural network. Further, the process involves learning by the soft-max classifier. The experiments are performed using three different datasets with 3K,10K and 100K tweets. The proposed approach represents a significant improvement in accuracy, precision, and recall in comparison to existing approaches.
PAKDD2020 Alibaba AI Ops Competition: An SPE-LightGBM Approach

This paper describes our submission to the PAKDD2020 Alibaba AI Ops Competition. We regard the hard driver disk failure prediction problem as a binary classification problem. Our approach is based on self-paced ensemble (SPE) [9] and a light gradient boosting machine (LightGBM) [8]. With three types of feature (raw feature, window-based feature and combined raw feature) and our proposed training sample selection strategy, our approach achieved rank 14 in the final standings with F-score (defined in [1]) of 0.37. The code for our approach can be found in https://github.com/fengyang95/Alibaba_AI_Ops_Competition_Rank14 .
Development of Mathematics Learning Device Based on Cooperative Model Type of Think Talk Write that Supported by Edmodo for Developing the Mathematics Problem Solving Skills

Abstract This research aims to gather the mathematics learning device based on cooperative model type of think talk write that supported by Edmodo that has a validity, practical, and effective as an effort to improve student problem solving skills on mathematics. This research classified as a type of design research by following the design research procedure by Plomp that includes preliminary phase, prototype phase, and assessment phase. The subject of this research are students of grade X of Senior High School Number 2 Negara, they are 20 students of grade X MIPA 4 for limited tests, 36 students of grade X MIPA 2 for field test I, and 36 students of grade X MIPA 1 for field test II. Learning device that developed are students’ books and teachers’ books that supported by Edmodo. Students book is a mathematics book that intended by the researcher is a mathematics book that discus the trigonometry for grade X. Results of the research shows that learning device that developed fulfilled the validity criteria, practically criteria, and effectivity criteria that expected. Characteristics on the students’ book and teacher’s book are interestingly designed and adapted to the syntax of cooperative model type of think talk write that supported by Edmodo.
Generalisations of stochastic supervision models

When the labelling information is not deterministic, traditional supervised learning algorithms cannot be applied. In this case, stochastic supervision models provide a valuable alternative to classification. However, these models are restricted in several aspects, which critically limits their applicability. In this paper, we provide four generalisations of stochastic supervision models, extending them to asymmetric assessments, multiple classes, feature-dependent assessments and multi-modal classes, respectively. Corresponding to these generalisations, we derive four new EM algorithms. We show the effectiveness of our generalisations through illustrative examples of simulated datasets, as well as real-world examples of three famous datasets, the MNIST dataset, the CIFAR-10 dataset and the EMNIST dataset.
The Status of Mind and Intellect in Digital Environment

The article examines the impact of digitalization on human life and intellectual experience. The development of computer technology demands an understanding of new aspects of human development and requires a capability to overcome not only external conditions but also ourselves. Entering a new level of development cannot imply a complete rejection of previous dispositions, but should be accompanied by reflection on personal experience and by the quest for new forms of interaction in society and with nature. Communicative and cognitive activity of a person has an ontological basis and relies on processes that actually evolve in nature. Therefore, the creation of new objects is always associated with the properties of natural material and gives rise to new points of support in the development of man. The more audacious his projects, the more important it is to preserve this connection to nature. It is always the human being who turns out to be the initiator who knows how to solve problems. The conformity of complex technical systems to nature is not only a goal but also a value of meaningful construction of development perspectives. The key to the nature orientation of the modern digital world is the human being himself, who keeps all the secrets of the culture of his natural development. Therefore, the proposed by the Russian philosopher V.S. Stepin post-non-classical approach, based on the principle of “human-sizedness,” is an important contribution to contemporary research because it draws attention to the “human – machine” communication, to the relationship between a person and technological systems he created. The article concludes that during digital transformation, a cultural conflict arises: in an effort to solve the problems of the future, a person equips his life with devices that are designed to support him, to expand his functionality, but at the same time, the boundaries of humanity become dissolved and the forms of human activity undergo simplification. Transhumanism engages society in the fight against fears of vulnerability and memory loss and ignores the flexibility and sustainability of natural foundation.