Reviewerly/exHarmony huggingface dataset:
AUTOMATIC IDENTIFICATION OF ARCHAEOLOGICAL ARTIFACTS ON THE EXCAVATION SITE

Abstract. Archaeological data is processed to ensure that it can be easily accessed and used. The integration of the documentation into GIS tools is carried out in the post-excavation phase. The final documents are completed on the basis of intermediate documents made on the excavation site. Time during the excavation is precious and any action that takes time is questioned to allow to devote a maximum of resources to the most important tasks. Many tasks are associated with a traditional paper entry. The aim of this study is to experiment with the use of means of automating the management of archaeological documents in order to minimize the repetition of recording acts of different kind. The integration of computer technology in the field is gradually being achieved through the use of tablets, but their use on the excavation site remains a strong constraint. The first task of this automation lies in the possibility of identifying objects of interest during the excavation. In order to make this recognition of archaeological entities possible it is necessary to ask when they are easily identifiable: in the excavation report. The hypothesis formulated here is that excavation reports can be used as a source for creating learning data sets of neural networks dedicated to the recognition of archaeological objects on site. Two important steps in automating the integration of archaeological data are presented here, the extraction of images and their semantics from excavation reports and the learning process of a neural network for the recognition of archaeological entities at the site of their discovery. The extraction of images and the identification of what they contain allows to enrich neural network learning datasets. Tests have been made to validate the ability of such tools to reliably identify particular objects. We chose CNN to test the ability to recognize archaeological objects in an excavation context. It is an image-based network. What is sought here is the ability to recognize an object for a neural network.
Minimal Similarity Loss Hashing based on Optimized Self-taught Clustering Method

In With the rapid growth of the amount of web images, how to fast respond the approximate nearest neighbors (ANN) search task has been concerned by researchers.As hashing algorithms map the floating point data into binary code and achieve ANN search task according to Hamming distances, it has the advantages of low computational time complexity.To obtain an excellent ANN search performance based on compact binary code, many algorithms adopt machine learning mechanism to train hashing functions.For instance, k-means hashing (KMH) and stacked k-means hashing (SKMH) utilize k-means clustering mechanism to learn encoding centers.Due to KMH and SKMH randomly generate initial centers, many centers would converge to the same solution.To fix the above problem, a novel hashing method termed as minimal similarity loss hashing (MSLH) is proposed to generate the initial centers with maximum average distance by a self-taught mechanism.Furthermore, MSLH defines both the similarity loss and the quantization loss as the objective function.By minimizing the similarity loss, MSLH can approximate the data pairs' Euclidean distance by their Hamming distance.The encoding results with minimal quantization loss map the nearest neighbors into the same binary code, which well adaptive to the data distribution.The ANN search comparative experiments on three public available datasets including NUS-WIDE and 22K LabelME show that MSLH can achieve a superior performance.
On Non-Supersymmetric String Model Building

We study a class of heterotic string compactifications possessing SO(10) "observable" gauge symmetry and spontaneously broken supersymmetry via the Scherk-Schwartz mechanism.We formulate a set of phenomenological criteria and identify models that comply with all requirements.This approach allows us to address and propose solutions to some of the open problems in non-supersymmetric string model building including the vacuum instability due to the appearance of tachyons and dilaton tadpoles, the presence of chiral fermions and the existence of Standard Model breaking light Higgs fields.
Multithreading Application for Counting Vehicle by Using Background Subtraction Method

Image and video processing has become important part in intelligent transportation system (ITS) application, especially for collecting road traffic data. Pictures that already collected by a charged coupled device (CCD) camera usually being processed by several image processing algorithms and the application’s code will be executed in a large number of iteration because many algorithms are getting involved in processing the frame which captured by the camera. Typical application will process the first frame until finish and then continue to the next frame, so the application must wait until the first frame being processed. If the algorithms that executed quite complex and have a significant running time there will be a dropped frame and the time difference between data acquisition and real time video is divided by large margin. We proposed an implementation of multithreading to boost the application performance so the data can be acquire in real time and every new frame could be processed in short time. The application performance before and after using a multithreading is known by comparing the data acquisition time that stored in the database. The application effectiveness could define by running a multiple video streaming in same resolution.
Evaluation of Data Mining Categorization Algorithms on Aspirates Nucleus Features for Breast Cancer Prediction and Detection

With the development of technology the use of Computer Aided Diagnosis has become a key for breast cancer diagnosis.It is important to increase the accuracy and effective of such systems.The concept of data mining can be applied on the data gathered through such systems for prediction and prevention of breast cancer.In this research, we have conducted the comparison between seven classification algorithms with the help of WEKA (The Waikato Environment for Knowledge Analysis) tool on the 569 instances (10 nucleus attributes) of data with two classes Malignant(M) and Benign (B) of breast cancer aspirate cells.Furthermore the influence of each attribute on prediction was evaluated.The accuracy of these algorithms was above 91% with the highest value of 94.02% for random forest and the predictive power of conclave points was highest whereas lowest was of Fractal Dimension.
Hand Gestures for Hearing Impaired and Inarticulate People using CNN

Gesture languages are an extremely important communication tool for many dumb and hard-of-hearing people.Sign languages are the native languages of the Deaf and Dumb community and provide full access to communication.Thanks to hearing ability we are able to perceive thoughts of every different.However, what if one fully cannot hear something and eventually cannot speak.So, the Gesture Language is that the main human action tool for hearing impaired and mute folks, associate degreed additionally to make sure a freelance life for them, the automated interpretation of linguistic communication is an in-depth analysis space.With the utilization of image process and artificial intelligence, several techniques and algorithms have been developed during this space.Each linguistic communication recognition system is trained for recognizing the gestures/signs and changing them into needed pattern.The projected system aims to produce speech to unarticulated, during this paper the double twohanded Indian linguistic communication is captured as a series of pictures and it's processed with the assistance of Python so it can produce speech and text as output.
Evaluating The Use of Information Technology in Computer Networks Lectures in The Era of Covid-19 Pandemic

The Covid-19 pandemic makes massive use of information technology (IT) in various fields. This study aims to evaluate the use of IT in Computer Networks lectures at the Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Riau in the era of Covid-19 Pandemic. This causal comparative study uses data from the results of student achievement in the Even Semester Academic Year 2019/2020. There are two lecture models given to students namely synchronous and asynchronous models. The use of the model is based on the type of lecture material provided. Furthermore, the results of student achievement obtained at the end of the semester are compared with the results of student achievement in the previous year that used physical face-to-face lectures. The results of this study indicate that there was an increase of 7.17% in the student achievement during the use of IT in lectures during the Covid-19 Pandemic with the effective synchronous lectures duration from 60 to 100 minutes. &#x0D;
Algorithms and complexity evaluation of 3- and 5-isogeny calculation of super singular Edwards curves

The properties and existence conditions of 3- and 5-isogenies for complete and quadratic super singular Edwards curves over the fields of p&gt;3 odd characteristic are analyzed. It is proposed to use the minimum odd degrees 3- and 5-isogenies for the task of keys encapsulation based on the SIDH algorithm of post quantum cryptography, which allows bypassing the problem of special points of the 2nd and 4th orders. These points always arise on 2-isogenies for the classes of noncyclic Edwards curves. A review of the main properties of the Edwards curve classes is given. An analysis of the properties of isogenies of odd degrees of Edwards curves with one parameter d in affine coordinates and examples of their calculation are given The known formulas of 3- and 5-isogeny in affine coordinates are transformed into projective coordinates. To increase the rate of isogeny calculation, only the x-coordinate of the affine point of the curve is used. Formulas for the coordinates and complexity evaluation for 3-isogeny calculations in the classes of complete and quadratic Edwards curves in projective coordinates are obtained. The parameter d of the curve was expressed in terms of the x-coordinates of the points of the nucleus for the 5th order nucleus, which allowed us to obtain formulas independent of d for the coordinates of 5-isogenies. A comparative analysis of the complexity of 4 algorithms for calculating the coordinates of 5 isogenies is carried out. Algorithms for computing 3- and 5-isogenies in the classes of complete and quadratic super singular Edwards curves are constructed. Some requirements for the parameters of the cryptosystem are considered.
Big data of the Babylonian library

The main goal of this article is to raise the question of the concept of Big data itself and the impact of this concept on various aspects of human cognition.The article is an attempt to comprehend the approaches to data processing and their relationship with each other.An assumption is made that the idea of Big data is embodied, in particular, in the image of the Babylonian library from the story of the same name by Jorge Luis Borges.
Geological Survey of New South Wales: New state-wide geophysical images for New South Wales

During 2019 the Geological Survey of New South Wales (GSNSW) undertook a refresh of publicly available geophysics by collating, cataloguing and quality-assuring all the company data acquired across...
Management Dysfunction in Optimizing the General Education System

The optimization of Russian secondary education carried out in 2010-2014 intending to strengthen the role of municipal authorities had some negative consequences. For instance, territorial educational authorities started receiving complaints about the violation of labor standards, and teachers began to quit their jobs. The purpose of this paper is to study the dependence of the dysfunctions manifested in the general education system on the management methods used by municipal authorities. The research method involves an all-Russian representative expert survey (2018) of specialists employed at territorial and municipal education authorities. The results of the study showed that the cause of destructive phenomena that had occurred in the field of work regulation of the general education system and made teachers quit their jobs was the domination of the administrative principle in the selection of personnel at the municipal level. The prescriptive management methods began to prevail at schools because the optimization of schools and changes in teacher standards in connection with higher teachers’ salaries were supervised by federal educational authorities, which stimulated municipal authorities to strengthen directorial management methods in the interests of the successful implementation of the optimization program. For this reason, municipal authorities began to select specialists with good managerial abilities, paying less attention to their creative side. The study showed that the priority of directive character in the work of municipal education administration bodies was generated by the excessive role of federal bodies in coordinating the territorial education system in labor-regulating and financial aspects. Conclusion: the federal system of general education management needs to be decentralized and creativity should be prioritized in the selection of specialists for municipal education authorities.
The research of performance of the “Cypress” lightweight block cipher on different platforms

М.Ю. РОДІНКО, Р.В. ОЛІЙНИКОВ, д-р техн
Worksheet for Application of Word Square Learning Models at Publik Junior High School Number I Kapur IX District

This research is motivated by negative activities that occur in the learning process such as students often in and out, telling stories, disturbing friends in Public Junior High School Number I (Sekolah Menengah Pertama Negeri /SMPN) I Kapur IX District.The purpose of this study is to find out the application of the word square learning model accompanied by student worksheet to the learning activities of VII2 graders of Social Sciences for Even 2018/2019 academic year.The method used in this research is descriptive qualitative type.The subjects in this study were students of class VII2 of 26 students.The technique of collecting observation data directly with sheets uses observation sheets.The results of this study show positive student activity in the learning process compared before using the work square learning model accompanied by student worksheet.The positive activity of students increases like listening, asking, reading, writing and enthusiasm in learning compared to learning before using the work square learning model accompanied by student worksheet.
Analisis Kekuatan Bangunan Rumah Terhadap Banjir Berdasarkan Interpretasi Bentuk Atap Mengunakan Sistem Informasi Geografis Di Desa Kaligayam, Kecamatan Margasari, Kabupaten Tegal

Flood events in Kaligayam Village occur due to rainwater and overflowing rivers trapped in sloping residential areas. Research on the quality of houses in the face of flooding, by grouping based on the shape of the roof, has not been widely carried out, especially in this research area. The use of GIS to analyze the condition of a house in an emergency situation can still be developed to get more detailed results. The population in this study was the house building unit, and the sampling method uses proportional techniques that were randomly selected. The sample of grouping is based on the roof shape of the house that was acquired with Quickbird image interpretation with 0.6 meter spatial resolution. The results of the acquisition of high-rise building data were built with supporting and validated data through field surveys. The database that is processed using GIS to produce data on classes of house buildings in watching flood data on physical conditions, support, and age of the house building. Inventory of all housebuilding parameter data produces a map of the quality of the house building against flooding. In each form of the roof, the building of the house has a variety of different levels of quality in the face of the danger of flooding. The level of quality of the house becomes five levels (very high, high, medium, low, and very low). The type of roof of the village becomes the type of building that has the best quality which is the type of house building with the highest resilience.
Learning Motivation In Street Children (Case Study on Street Children Who Attend School in Public Elementary School (Sekolah Dasar Negeri/SDN) Mawar 2 Banjarmasin)

Street children are children who spend most of their daily activities on the road.They get different treatment from the community.Their lives are very close to juvenile delinquency.However, in Central Banjarmasin District street children prefer to work as well as school.This study aims to 1) Explaining the motivation of street children in SDN Mawar 2, 2) Describe the school's response to the presence of street children in SDN Mawar 2. The case study method used in the study.The data collection technique involves three stages; observation, interview, documentation.Data analysis started with the reduction, presentation, and verification of data.The results of the research are: 1) motivation to study street children in SDN Mawar 2 (Sekolah Bawang) Banjarmasin based on internal factors do not have a meaningful impact.On the contrary, In the external factors of students affected by economic conditions that make it "leaves" the obligation to attend school.2) SDN Mawar Banjarmasin implements the rules and regulations.Schools do various efforts to enable them to rebuild the motivation to learn.School efforts in providing education to street children were able to improve the knowledge, skills, and attitudes as well as learn the art and culture.Schools do various efforts to enable them to rebuild the motivation to learn.School efforts in providing education to street children were able to improve the knowledge, skills, and attitudes as well as learn the art and culture.Schools do various efforts to enable them to rebuild the motivation to learn.School efforts in providing education to street children were able to improve the knowledge, skills, and attitudes as well as learn the art and culture.
Updating the dictionary: Semantic change identification based on change in bigrams over time

We investigate a method of updating a Danish monolingual dictionary with new semantic information on already included lemmas in a systematic way, based on the hypothesis that the variation in bigrams over time in a corpus might indicate changes in the meaning of one of the words. The method combines corpus statistics with manual annotations. The first step consists in measuring the collocational change in a homogeneous newswire corpus with texts from a 14 year time span, 2005 through 2018, by calculating all the statistically significant bigrams. These are then applied to a new version of the corpus that is split into one sub-corpus per year. We then collect all the bigrams that do not appear at all in the first three years, but appear at least 20 times in the following 11 years. The output, a dataset of 745 bigrams considered to be potentially new in Danish, are double annotated, and depending on the annotations and the inter-annotator agreement, either discarded or divided into groups of relevant data for further investigation. We then carry out a more thorough lexicographical study of the bigrams in order to determine the degree to which they support the identification of new senses and lead to revised sense inventories for at least one of the words Furthermore we study the relation between the revisions carried out, the annotation values and the degree of inter-annotator agreement. Finally, we compare the resulting updates of the dictionary with Cook et al. (2013), and discuss whether the method might lead to a more consistent way of revising and updating the dictionary in the future.
Optimization of polynomial multiplication algorithm for NTRU-like algorithms

The problem of cryptographic protection against classical and potential crypto-analytic attacks with the use of quantum computer and quantum mathematics has become an urgent issue. Understanding this problem, technologically advanced states are making significant efforts to analyze the cryptographic stability of existing standards for cryptographic information security in the post-quantum period and are seeking to establish post-quantum standards for asymmetric cryptography. A practical solution to this problem is being pursued globally during the NIST USA international competition. As previous studies have shown, algebraic lattices are now considered to be a reliable mathematical basis on which post-quantum asymmetric encryptions and PIK can be created. NTRU-like algorithms are a class of crypto-transformations algorithms that satisfy basically the requirements of post-quantum cryptography. Algorithms for key generation direct and reverse cryptographic transformations are the basic components in NTRU-like algorithms for asymmetric crypto-transformations. A number of authors today focus on optimizing polynomial multiplication for these algorithms by the criterion of time complexity. A special requirement for them is the independence of the time of the multiplication operation from the polynomials themselves, which makes it impossible to attack by side channels. This paper proposes the use of the NTT and Toom-Kuk algorithms. It proposes a new solution to this problematic issue, which made it possible to obtain an acceleration of almost 2 times while providing a constant polynomial multiplication time. The objective of this article is to optimize the polynomial multiplication algorithm by the time complexity criterion, used to generate keys and perform direct and reverse cryptographic transformations of asymmetric encryptions and PIK on algebraic lattices.
Photonic architecture for reinforcement learning

Reinforcement learning algorithms are a powerful tool to manage the interaction between a system and its environment. Here we present an approach to apply these algorithms within modern-day photonic technologies. Numerical tests, performed on typical learning tasks, show that the architecture is robust against experimental noise, which can even be beneficial for the learning process. The proposed architecture, based on single-photon evolution on a tree structure of tunable beamsplitters, is simple, easy to implement and an integration in quantum optics applications appears to be within the reach of near-term technology.
Online Theory Supplement to "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks"

This online theory supplement has three sections.First section provides the main lemmas needed for the proofs of Theorems 1-3 in Appendix A of the paper.Second section contains the complementary lemmas needed for the proofs of the main lemmas in the previous section.Third section explains the algorithms used for implementing Lasso, Adaptive Lasso and Cross-validation.Notations: Generic …nite positive constants are denoted by C i for i = 1; 2; and c.They can take di¤erent values in di¤erent instances.kAk 2 , kAk F , kAk 1 and kAk 1 denote the spectral, Frobenius, row, and column norms of matrix A, respectively.i (A) denote the