Reviewerly/exHarmony huggingface dataset:
AMASS: Automated Software Mass Customization via Feature Identification and Tailoring

The rapid inflation of software features brings inefficiency and vulnerabilities into programs, resulting in an increased attack surface with a higher possibility of exploitation.In this paper, we propose a novel framework for automated software mass customization (AMASS), which automatically identifies program features from binaries, tailors and eliminates the features to create customized program binaries in accordance with user needs, in a fully unsupervised fashion.It enables us to modularize program features and efficiently create customized program binaries at large scale.Evaluation using real-world executables including OpenSSL and LibreOffice demonstrates that AMASS can create a wide range of customized binaries for diverse feature requirements, with an average 92.76% accuracy for feature/function identification and up to 67% reduction of program attack surface.
LIBRARY IN A CULTURAL LANDSCAPE OF THE CITY (ON THE EXAMPLE OF ULAN-UDE)

Е.А. Кучмурукова, Ю
Proving skills in geometry of secondary grammar school leavers specialized in mathematics

We examined the evolution of the van Hiele level of some study groups specialized in mathematics from 2015 to 2018, then selected two of these groups and measured the students' proof skills by Zalman Usiskin's proof test.We examined whether students were able to read from the text of the statement the given fact and the fact to be proved, whether they were able to draw a figure and, using the labels, whether they were able to perform a simple proof requiring 2-3 steps.
Entrepreneurship in Small and Medium Enterprises: A Catalyst for Capacity Building and Sustainable Youths Employment Generation in the Federal Capital Territory, Abuja, Nigeria

This study investigated whether entrepreneurship in Small and Medium Enterprises (SMEs) can be a facilitator for capacity building and sustainable youth’s employment generation in the Federal Capital Territory, Abuja, Nigeria. The study used the survey research design. A structured questionnaire was employed for the collection of data. The views of 100 SMEs entrepreneur selected through the purposive sampling technique were elicited on whether entrepreneurship in SMEs can promote capacity building and sustainable youth’s employment generation in Abuja. The results showed that that entrepreneurship in SMEs can facilitate capacity building and sustain employment generation among youths in Abuja. However, the study revealed that entrepreneurship in SMEs can contribute effectively to the provision of capacity building and sustainable job for youths in Abuja. The finding revealed that access to finance was identified as the greatest barrier facing SMEs entrepreneur in the generation of sustainable employment for youths. Furthermore, the main channels through which SMEs entrepreneur create job for youths in the study area were becoming drivers of innovation and becoming the engine of economic growth. The results showed that entrepreneurship in SMEs is a catalyst for capacity building and sustainable youth’s employment generation in the Federal Capital Territory, Abuja. The study, therefore, recommends that: besides the microfinance banks, entrepreneurship development banks should be established with a view to providing fund to support SMEs and other enterprises in general and the government should provide the enabling environment for SMEs entrepreneur to thrive.
A Construction of Rotated Lattices via Totally Real Subfields of the Cyclotomic Field Q(z_p)

The theory of lattices have shown to be useful in information theory and rotated lattices with high modulations diversity have been extensively studied as an alternative approach for transmission over a Rayleigh-fading channel, where the performance of this modulation schemes essentially depends of the modulation diversity and of the minimum product distance to achieve substantial coding gains. The maximum diversity of a rotated lattice is guaranteed when we use totally real number fields and the minimum product distance is optimized by considering fields with minimum discriminant. In this paper, we present a construction of rotated lattice for the Rayleigh fading channel in Euclidean spaces with full diversity, where this construction is through a totally real subfield K of the cyclotomic field Q(z_p), where p is an odd prime, obtained by endowing their ring of integers.
PERANCANGAN SISTEM INFORMASI ELECTRONIC NEW STUDENT REGISTRATION STUDI KASUS LEMBAGA BAHASA DAN PENDIDIKAN PROFESIONAL (LBPP) LIA PRAMUKA JAKARTA

The rapid development of information technology can meet a variety of human activities and needs, the use of computers can provide the effectiveness of a good life for humans, besides that with a computer someone is able to create a useful technological system. Today's internet technology has the privilege of finding information in other parts of the world without being hindered by distance, time and place. Based on the background stated above, with this the author tries to design a new student registration website, so that it can partially replace the role of the new student registration officer. The design of this web application will provide many conveniences in the process of registering new students, especially for students or parents who have a busy schedule so that registration of prospective students can be done online. This system provides an information that is registration activities for prospective new students, LIA profiles, verification and announcements of level placement at the Institute of Language and Professional Education (LBPP) LIA Pramuka Jakarta.
Image inpainting based on low-rank ALM algorithm

Image inpainting is the process of reconstructing lost or deteriorated part of images based on priori knowledge or background information. In this paper, we use a low-rank structure with global information to fix the image, the Augmented Lagrange Multiplier(ALM) to optimize our algorithm. We use the Alternating Direction Method of Multipliers(ADMM) to solve image inpainting problems. According to our experiments, information of image scenes is dominated by the largest singular value of the previous small part. Inspired by this, we use the characterize top 20 largest singular values of the information to repair the image. Our experimental analyses show that, using our method to repair images is better than previous traditional method.
Regularized Training Framework for Combining Pruning and Quantization to Compress Neural Networks

Many convolutional neural networks(CNNs) have been proposed to solve computer vision tasks such as image classification and image segmentation. However the CNNs usually contain a large number of parameters to determine which consumes very high computation and power resources. Thus, it is difficult to deploy the CNNs on resource-limited devices. Network pruning and network quantization are two main methods to compress the CNNs, researchers often apply these methods individually without considering the relationship between them. In this paper, we explore the coupling relationship between network pruning and quantization, as well as the limits of the current network compression training method. Then we propose a new regularized training method that can combine pruning and quantization within a simple training framework. Experiments show that by using the proposed training framework, the finetune process is not needed anymore and hence we can reduce much time for training a network. The simulation results also show that the performance of the network can over-perform the traditional methods. The proposed framework is suitable for the CNNs deployed in portable devices with limited computational resources and power supply.
Identification of Parameters of One Fractional Model of Soluble Substances Migration

The paper deals with the problem of identification of model parameters in the case of mathematical modeling of fractional-differential dynamics of anomalous process of convective diffusion of soluble substances under steady-state profile groundwater filtration with a free surface. We describe the process of mass transfer using a model containing a generalized fractional derivative of Caputo-Gerasimov with respect to the time variable while the filtration process is considered in the potential velocity field. Since the filtration domain is a domain with a partially unknown boundary, the solution of the problem is performed using an anticipatory transition to a completely determined complex potential domain with a known characteristic flow function. We pose the problem of identification of the values of the parameters of a generalized fractional derivative based on the measurements of substance concentration. Such an approach allows us to more adequately describe the processes of mass transfer in environments with a complex spatial and temporal structure, including soils, in the situation of significant costs needed for their exact geophysical analysis. Taking into account the complexity of the solution of inverse problems for differential equations with fractional derivatives, the fixed quantity and continuity of optimized parameters, it is proposed to use a meta-heuristic particle swarm optimization algorithm for their identification. The paper briefly describes the finite-difference method of the approximate solution of the direct problem, poses the problem of parameters identification, and describes the modification of the used particle swarm optimization algorithm. We present the results of computer experiments that show the efficiency of the particle swarm optimization algorithm for determining the parameters of the fractional derivative, as well as the fact that, depending on the type of functional parameter of the generalized fractional derivative, the model allows describing both «ultra-slow» and «ultra-fast» diffusion modes.
Confidential State Verification for the Delegated Cloud Jobs with Confidential Audit Log

Cloud computing provides versatile solutions that allow users to delegate their jobs.An apparent limitation of most cloud audit services is that it is di cult for cloud users to tell the state of a delegated job.Although cloud users can provide a user-speci ed model, the model is susceptible to various exploits.In this paper, we present VERDICT, a system that ampli es the capability of the existing cloud audit services and allows users to check the state of a cloud job through the con dential model and audit log.VERDICT extracts the model from an application and keeps it in the encrypted form.The encrypted model is partitioned and updated with homomorphic encryption cipher in multiple sandboxes.The state of a delegated job can be checked by cloud users at any time.We implement VERDICT and deploy it in the VMs and containers on popular cloud platforms.Our evaluation shows that VERDICT is capable of reporting the state of a cloud job at run time, keeping the model con dential, and detecting malicious operations.
Virtual assistance information model for public services

Currently, the world and Russia are rapidly developing the direction of developing virtual assistants. This is primarily due to the demands of business, the state and the population for this product, as well as the development of technologies capable of high-quality implementation of this product. Offers on virtual assistants for business and the public exist in large numbers: Google Assistant, Microsoft Cortana, Siri, etc. At the same time, there are no ready-made solutions for state needs in the market. The task of navigating public services today is the most relevant and relevant for the public sector. Solving this problem using a virtual assistant will save billions of rubles a year across the country. The article proposes an information model for the implementation of a virtual assistant for navigating public services. The basis of the intelligence of the developed virtual assistant is made up of artificial neural networks. The developed virtual assistant information model is implemented in the VIka software product. The trial operation of VIka takes place on the website of the administration of the Khanty-Mansiysk Autonomous Okrug Yugra, located at https://vi.admhmao.ru/chat/new.php. To date, VIka can help navigate services in 10 areas, such as healthcare, utilities, a line to kindergarten, etc.
A method for converting entropy to inclusion measure of interval type-2 fuzzy sets

Abstract As tools for dealing with universal fuzziness in human thinking, traditional fuzzy sets, namely type-1 fuzzy sets, are not able to directly model uncertainties about membership functions, however type-2 fuzzy sets can make up for this deficiency. Interval type-2 fuzzy sets, the simplified cases of general type-2 fuzzy sets, are practical because its membership functions and operations are greatly simplified. The inclusion measure and entropy of fuzzy sets are two important parameters with application prospects, the former describes the degree to which a fuzzy set is included in another, the latter shows the quantity of fuzzy information in a fuzzy set. It is important to make in-depth research on the two measures. In this paper, we mainly discuss the relationship of the inclusion measure and entropy of interval type-2 fuzzy sets proposed by Zheng et al., and present a theorem that converts the entropy to the inclusion measure of interval type-2 fuzzy sets. The conclusion provides the basis for further research.
Improvement of Flexible Testifying System of Civil Procedure Witnesses under the Background of Deep Integration of Internet Technology

It has become a trend to use information technology to realize witness covert testimony and remote testimony in civil litigation, which is efficient, convenient and obvious. But at the same time, due to the imperfection of relevant systems, the actual application of covert testimony and remote testimony is not standardized, and there are many problems in judicial practice. This paper analyzes the existing problems of flexible testimony and puts forward some ideas to improve the system of flexible testimony.
Hate Speech: Forensic Linguistics Study

The article entitled "Hate Speech: Forensic Linguistics Study" aims to describe the hate speech delivered by the speaker to the speech partner.The hate speech analyzed in this article is sourced from videos and Facebook that were viral in the mass media in April 2019.Their content is content insulting to the President of the Republic of Indonesia, Joko Widodo.Data collected by the documentation method, then analyzed using the pragmasemantic approach.From the results of the analysis it was found that the hate speech spoken and / or written by B found that the utterances spoken through the video proved to violate the Information of Electronic Transactions Law.Through spoken and written words after being analyzed with a pragmasemantic approach, the preacher is proven to be hateful and threatened to be sent to prison with a minimum sentence of six years.Through lexical and contextual meaning, words, phrases, sentences, and discourse in video uploads, it was revealed that all the language elements contained in the data source proved to contain excactly meanings and aimed at insulting the speech partners.Speech hatred aimed for deliver feeling dislikes, hate, and humiliation to anybody else.
Method of Circle Time In Developing Skills of Children Talking In Kindergarten

This study aims (1) method for learning the circle time method for learning in Kindergarten, (2) to know how to speak to children before and after treatment in kindergarten, (3) find out the circle time method influence children's speech skills in Kindergarten. The focus of this study is the applica
FEATURES OF APPLICATION OF V-MODEL IN DEVELOPMENT AND ESTIMATION OF MEASURING INSTRUMENTS SOFTWARE

The research results of the features of the use of the V-model in the development and evaluation of the quality of software of measuring instruments (MI) were presented. The analysis of the possibility of using a cascade software development strategy and its application to assessing the quality of the software being developed was carried out. It is difficult to implement a classical cascade model in its pure form, therefore, variants of such a model with feedback between its separate stages was developed. The disadvantages and advantages of the V-model, which supports the cascade strategy of one-time execution of software development stages, are considered. The main purpose of the V-model is to provide planning testing software in the early stages of its development. V-model is aimed at simplifying the understanding of the complexity of software development. It is used to determine a single procedure for developing software, hardware and user interface. To reduce the shortcomings of the cascade strategy, a number of modifications of the V-model have been developed due to the type of feedback that provides the ability to modify the results of the previous stages of development. Specific guidelines and recommendations of international and regional organizations for legal metrology have been used to determine the components for quality assessment of MI software. The tasks of developing a MI software on the left side of the letter V begin with the definition of requirements to the MI itself, then to the MI software, and only then as a traditional software development. The V-model of the development and evaluation of the MI software quality is proposed, which allows you to adapt this model to a particular MI at the very beginning of the software development. It takes into account all the specific components of software testing for the MI. The degree of verification of the components of the MI software depends on the risk classes that are assigned to the software, depending on the MI for which it is created. The V-model of development and quality assessment of software of MI which takes into account all the specific components of the test are presented.
Automated Music Making with Recurrent Neural Network

Today, the growing market of entertainment has placed a higher demand for music.Quality music is essential for video making, video game making, or even in any public places.However, sometimes finding a suitable list of music can be hard and expensive.This may be solved by automatic, deep-learning based music making.Using Recurrent Neural Network, computers are able to learn the patterns from existing music pieces and convert them to a possibility map.Companies like Google, Sony, and Amper are creating their applications for music generation.We plan to set up a platform where generating music can be done and retrieved directly online.With different options for genre and length, the users can conveniently generate music that fits their needs.
Penerapan Metode Association Rule Untuk Menganalisa Pola Pemakaian Bahan Kimia Di Laboratorium Menggunakan Algoritma FP-Growth (Studi Kasus di Laboratorium Kimia PT. PLN (Persero) Sektor Pembangkitan Belawan Medan)

&lt;p class="Default"&gt;&lt;em&gt;The pattern of using chemicals in the laboratory of PT. PLN (Persero) &lt;/em&gt;&lt;em&gt;Sektor Pembangkitan &lt;/em&gt;&lt;em&gt;Belawan Medan is not only to find out what chemicals are used but also to find out the amount of chemicals left so that laboratory officials can properly manage the use of these chemicals. One appropriate way to determine the pattern of use of these chemicals is to use data mining techniques. The Data Mining technique used in this case is the FP-Growth Algorithm. FP-Growth is an alternative algorithm that can be used to determine the most frequent set of data in a data set. The study was conducted using several variables, namely the date and chemicals used. The results of this study are in the form of a chemical usage pattern which is processed using software, namely implementing the FP-Growth algorithm using the concept of FP-Tree development in searching for Frequent Itemset.&lt;/em&gt;&lt;/p&gt;&lt;p class="Default"&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;&lt;pre&gt;&lt;em&gt;Keywords: Data Mining, Association Rules, Frequent Itemset, FP-Growth&lt;/em&gt;&lt;/pre&gt;
A Channel Coding Scheme for 2400 bps Speech Coding Algorithm

In recent years, low-rate speech coding algorithms have been extensively and deeply studied, but as the coding rate decreases, the robustness of the speech coding algorithm to channel error is getting worse. In order to improve the robustness of low-rate speech coding algorithm to channel error, this paper proposes a channel coding algorithm based on source characteristics. The algorithm is based on MELP 2400 bps speech coding algorithm, and analyzes the importance difference between the coded bits and the synthesized speech quality, which are divided into important bits, sub-important bits and general bits. Different BCH channel coding schemes are employed for the three types of coded bits. Simulation experiments show that the channel coding scheme combined with bit importance has better anti-error effect under different random error rates.
The analysis of facial feature deformation using optical flow algorithm

&lt;span&gt;Facial features deformed according to the intended facial expression. Specific facial features are associated with specific facial expression, i.e. happy means the deformation of mouth. This paper presents the study of facial feature deformation for each facial expression by using an optical flow algorithm and segmented into three different regions of interest. The deformation of facial features shows the relation between facial the and facial expression. Based on the experiments, the deformations of eye and mouth are significant in all expressions except happy. For happy expression, cheeks and mouths are the significant regions. This work also suggests that different facial features' intensity varies in the way that they contribute to the recognition of the different facial expression intensity. The maximum magnitude across all expressions is shown by the mouth for surprise expression which is 9x10&lt;sup&gt;-4&lt;/sup&gt;. While the minimum magnitude is shown by the mouth for angry expression which is 0.4x10&lt;sup&gt;-4&lt;/sup&gt;.&lt;/span&gt;
An Analysis of Item Difficulties in PBT for the Graduate Candidates of IAIN Bukittinggi

this research aimed at finding out the item difficulties of the listening, structure and written expression, and reading comprehension in Paper Based TOEFL (PBT) conducted at IAIN Bukittinggi.The most problematic issue in IAIN Bukittinggi is the TOEFL score.The mean score for the graduate candidates for the bachelor degree and diploma was 357.Based on the passing grade set by the institution, the graduate candidates should get at least 400.This is a descriptive quantitative research with the 1035 graduate candidates as the population.The total sampling was used to determine the sample.Item difficulty index is used to determine the classification of each item in the PBT.The result of the research shows that all of the items in the PBT test were considered difficult and moderate, none of the item was considered easy.It means that the PBT is very difficult for the students.This is the reason why the graduate candidates could not achive the passing grade set by the institution Keywords.item difficulty