Reviewerly/exHarmony huggingface dataset:
DARK WEB AS A CONTEMPORARY CHALLENGE TO CYBER SECURITY

Inspiration for work: This paper looks specifically at the dark net which has become notorious in the media for being a hidden part of the web where all manner of illegal activities take place. Precisely, it draws attention to the ‘black market’ of the Internet–the dark web that represents such a hidden space, being the largest deployed anonymity network. Goals of paper: This article analyzes and highlights the major roles played by the Dark Web as a market; as a communication platform; as an enabler of cybercrime; as an enabler of anonymous financial transactions and as a proxy to a surface web. Methodology/Concept: The paper is managed by looking at current literature in academic journal databases and own research in dark web. The motivation behind this literature review is to estimate the current state and development of the dark web in relation to the roles it plays and explore how the dark web enables cybercrime. Limits of the research/work: It contributes to the space of the dark web by assisting as a citation document and by suggesting a research agenda to renew study on this phenomenon and allow for better projections on how it may reveal over time and as technology expands. Results/Conclusions: Criminality on the dark web spans multiple areas and involves a wide range of criminal commodities. An effective countermeasure will therefore require a suitably coordinated, cross-cutting response, involving investigators with equally diverse expertise. This will likely require additional capacity building and training of officers not involved in computer crime. And while though this awareness may not necessarily stop national security threats from the Dark Web, it can certainly shine a spotlight on the issue and facilitate a larger conversation on how the global community can address these emerging threats. Accountability of the research: The unique nature of Dark Net markets as highly anonymous and secretive, as well as loyal and intelligent, makes them an ideal test case for the unrestrained online market-place. There is a need for a global strategy and accountability to address the abuse of the dark web and other emerging platforms for illicit trade.
Management Skills of Financial Resources and Learners’ Access to Quality Education

Currently, many developing and developed nations have been developing and implementing policies that are perceived to improve the state of Early Childhood Education in various countries (Kang'e the, Wakahiu & Michael, 2015), this has galvanized many countries, especially in sub-Saharan Africa (SSA), into confronting their historically low access to quality early childhood education (Murunga, 2015).This has brought a remarkable success in attracting many children into schools (UNESCO, 2014).However, filling the classrooms is not enough in the process of ensuring access to basic education and Education for all.The goal is geared towards having positive social and economic returns in which
Model of Primary School Teachers Training for Work in the System of Inclusive Education by Applying Extrapolation of Poland’s Advances in Training for Work

The purpose of the study was to develop a model of vocational training of primary school teachers for work in the system of inclusive education by applying extrapolation of Polandâ€™s advances in training for work and to identify how it was evaluated by the experts in Pedagogics. The study was based on four stages which were as follows: a baseline study, model design, and description, expert evaluation, and analyses. The baseline study aimed at analysing the secondary education system in the Republic of Poland, and a teacher training system of inclusive education. The model was evaluated by experts using the questionnaire. The reliability score was 0.93 which was appropriate for this field of study. The SPSS Software (version 20) was used to analyse the data. The multiple-choice questions that were based on a five-point Likert scale were analysed using means and standard deviations. The data drawn from the open-ended questions were analysed using frequency distributions. Mann-Whitney U test calculator was employed to compare attitude score differences between the respondentsâ€™ categories. A Chi-square test was used for the computation of the data between the groups of respondents. P-value of p&lt;0.05 was considered sufficient. The proposed model could be considered a benchmark for the professional training and consists of four blocks: value and objective, theory and best practices-related, content-based and procedural, productive. The designed model requires a rethinking and adaptation to the conditions of the system of higher education in Ukraine. Further research is needed in testing its effectiveness. https://doi.org/10.26803/ijlter.19.3.19
An Improvement Algorithm for the Image Compression Imaging

Lines and textures are natural properties of the surface of natural objects, and their images can be sparsely represented in suitable frames such as wavelets, curvelets and wave atoms. Based on characteristics that the curvelets framework is good at expressing the line feature and wavesat is good at representing texture features, we propose a model for the weighted sparsity constraints of the two frames. Furtherly, a multi-step iterative fast algorithm for solving the model is also proposed based on the split Bergman method. By introducing auxiliary variables and the Bergman distance, the original problem is transformed into an iterative solution of two simple sub-problems, which greatly reduces the computational complexity. Experiments using standard images show that the split-based Bergman iterative algorithm in hybrid domain defeats the traditional Wavelets framework or curvelets framework both in terms of timeliness and recovery accuracy, which demonstrates the validity of the model and algorithm in this paper.
Term based semantic clusters for very short text classification

Very short texts, such as tweets and invoices, present challenges in classification. Such texts abound in ellipsis, grammatical errors, misspellings, and semantic variation. Although term occurrences are strong indicators of content, in very short texts, sparsity makes it difficult to capture enough content for a semantic classifier A solution calls for a method that not only considers term occurrence, but also handles sparseness well. In this work, we introduce such an approach for the classification of short invoice descriptions, in such a way that each class reflects a different group of products or services. The developed algorithm is called Term Based Semantic Clusters (TBSeC).
ASSESSMENT OF COMPETENCE FORMATION IN THE COURSE OF STUDYING THE DISCIPLINE " HISTORY»

Due to the emergence of new generation standards, the modern education system is undergoing significant changes that are aimed at finding new approaches to learning. Unfortunately, the quality of training of graduates of professional educational institutions still does not match the level of development of modern technologies. This article is devoted to the problems of assessing the competence of students in the course of studying the discipline "History".
Students’ perception of bilingualism use in a classroom at senior high school: a case study

English is a language that is normally used around the world. It is the legitimate language of 53 nations. Thus, many people want to learn English. Bilinguals are present in every country, social class, and the global economy. It is demonstrated by bilingual class or two languages (English and Indonesian) class, which is really popular in Indonesia . O ne of the levels which provide s bilingual class is the level of senior high school . English is not only taught in English subject, but also in the other subjects . Th is research addressed the students' perception of the use of bilingualism in the teaching and learning process at senior high school. A qualitative approach as a basic framework was used in this research with a case study method. The participants of this research were 20 students of female and male. The data were taken with a questionnaire and interview. There were only three students involved in the interview session. The results show that  m ost students gave positive perceptions of the use of English ; understanding the explanation easily, feeling comfortable during the class, and enriching their vocabulary . This research can contribute to the policy-making of schools which intend to adopt a bilingual education program.
Penerapan Konsep Kota Pintar dengan Cara Penerapan ERP (Electronic Road Price) di Jalan Ibu Kota DKI Jakarta

The problem raised in this research is the implementation of ERP (Electronic Road Price) which will be applied in several street corners of the capital of Jakarta, many pros and cons that will occur in its application, ranging from its licensing to its application in the field, socialization to users the road in the capital is very important to do because it will directly intersect with motorized motorists in the capital of Jakarta, in its application also must be considered using what tools are best placed in every corner of the capital to help smooth the system to be applied, in this research the author will provide suggestions and frameworks so that the implementation of the ERP system (Electronic Road Price) can be carried out right away, with the suggestions that have been made are expected to influence the policies that will be made in terms of ERP (Electronic Road Price) in the future.
An optimal end-to-end training strategy for multi-expert-based neural architecture

Recently, we introduced a state-of-the-art object detection approach referred to as Multi-Expert R-CNN (ME R-CNN) that featured multiple expert classifiers, each being responsible for recognizing objects with distinctive geometrical features. The ME R-CNN architecture consists of multiple components: a shared convolutional network, Multi-Expert classifiers (ME), and Expert Assignment Network (EAN). Both ME and EAN take as a common input the output from the convolutional network and also use each other's output during training. Thus, it is quite challenging to properly train all the components simultaneously to globally optimize the network parameters. The main innovation of the proposed work is to optimize the entire architecture by using a novel training strategy in which manually associated 'RoI-to-expert' mapping is used instead of using the direct output of ME for training EAN. Our experiments show that the proposed training strategy speeds up training time at least 4.2x while maintaining comparable object detection accuracy.
THE SCIENTIFIC HERITAGE OF THE PROMINENT ESTONIAN LINGUIST MATI HINT

The scientific views of the famous Estonian linguist, public figure and politician, legendary professor of the University of Tallinn, Mati Hint (1937-2019), cover a wide range of Estonian philology, from phonetics to linguistic politics and the research of linguistic landscape. The number of his scientific works is well over 300. Mati Hint was characterized by a constant opposition to the mainstream. He popularized the South Estonian Tartu literary language, which had become extinct at the beginning of the 20th century, by publishing several scientific articles on this subject. Hint provided an innovative description of the phonological system, morphophonology and the grade alternation of the Estonian language. According to his concept, in the Estonian language, three longitudes of phonemes cannot be distinguished. Three longitudes can have a syllable. Thus, Estonian is not an unique language that differs from all other languages of the world, but on the contrary, it fits perfectly into all languages of the world. In many works he explains the problems of contacts between the Estonian and the Russian languages. Hint indicates the consequences of bilingualism, which may result in semilingualism, and in extreme cases in a language shift. A large language can be pidginized and creolized. According to the current period, professor Hint attributed to the English language similar roles in relation to Estonian, which he attributed to the Russian language during Perestroika.
Semiotic Analysis of the Political Advertisements of APC and PDP Presidential Candidates in the 2015 Elections in Nigeria

IntroductionOver the years, scholars have pontificated on political advertising and its influence on elections.While some of the studies argue that political advertising is a strong determinant of success or failure of political candidates; others believe that it has minimal or no effect.For instance, Okigbo (1992.p.5) asserts that "elections are won and lost largely on the ability of the campaign managers to use communication effectively".Also, in their study of Brazilian governorship election campaigns, Silveira & Mello cited in Olujide, Adeyemi & Gbadeyan (2011, p.7) found that "TV exposure in gubernatorial election has a strong effect in election outcomes, both statistically and practically".They contend that advertising has a greater impact when voters are uneducated and have access to TV.But Jowei and Dropp (2010) cited in Olujide, Adeyemi & Gbadeyan (2011) differ in the above claims.They argue that political advertisements generally, have a partisan tone and thus they can cause asymmetric partisan effects and turnout.They contend that the election that produced Barak Obama as the president of the United States of America was not strictly dependent on his heavy investment in advertising.According to them, "an Obama-funded ad will generally mobilize core Democrats, while demobilizing Republicans, so the net effect on the aggregate turn-out across the entire electorate is nebulous" they maintain.The bottom line of this argument is that there is a possibility that individual turn-out decisions in response to political advertisements may hinge on partisan considerations, and not on how persuasive it is.Not-withstanding the conflicting results of studies in political advertisement and its influence on voters' choice, the fact remains that political advertising has come to be an integral part of contemporary electioneering.According to M'bayo, Amobi &Sunday (2014, p .61), prior to the year 1963, political advertisement was almost non-existent in Nigeria, as political communications then were limited to rallies, soap box speeches and to some extent, editorial efforts.But in 1963, Chief Obafemi Awolowo, then leader of the defunct Action Group, went into the skies to send political messages during rallies, as noted by (Nzeribe 1991).For obvious political reasons, the 'skywriting'was neither sustained nor improved upon until the year 1990, when Nigerian politicians became aware of the power and effectiveness of political advertisements (Opeibi 2006).He observes that since 1990, Nigerian politicians have been using political advertisements as a major persuasive strategy in canvassing support during elections.The truth of the matter is that the
Deep net route generation is faster than a bullet

Recent breakthroughs in deep net processing have shown the ability to compute solutions to physics-based problems such as the three-body problem many orders-of-magnitude times faster. In this paper, we show how a deep autoencoder, trained on paths generated using a dynamical, physics-based model can generate comparable routes much faster. The autogenerated routes have all the properties of a physics-based model without the computational burden of explicitly solving the dynamical equations. This result is useful for planning and multi-agent reinforcement learning simulation purposes. In addition, the fast route planning capability may prove useful in real time situations such as collision avoidance or fast dynamic targeting response.
ANALYSIS OF SoDCONFLICTS IN SAP ERP SYSTEM LOGISTICS WITH THE USE OF THE SAP GRC APPLICATION

Background: Nowadays, the management and integration of various areas in an enterprise require the implementation of an adequate IT system.There are many such systems, often intended for enterprises of various sizes and industries.An example of an integrated IT system which offers comprehensive support to logistic processes is SAP ERP.In order to perform the different tasks, it is necessary to allocate relevant permissions to system users.Permission management in IT systems is necessary for protecting data against accidental, malicious manipulations, damage or unintentional wrong use. Methods:The analysis of users' permissions in SAP ERP and identification of SoD conflicts, if any, is performed automatically in practice, with the use of analytical tools matching the task.In order to get full control over the process of conflict identification and resolution, managing staff decide to implement the appropriate tool of the GRC (Governance Risk and Compliance) class.One of the solutions of the type is the dedicated SAP solution -SAP GRC Access Control.The SoD conflict matrix identified in the analysis is translated into so-called Rulebook written in the form of a specialist scheme integrated with the SAP GRC application.The set contains information about the business processes going on in the enterprise (e.g.materials management or purchases), identified business functions (e.g.acceptance of orders or stock taking exercises) and conflicts.It also includes, inter alia, identifiers of conflict creating functions, their level and type as well as the status of activity in the system (on / off).
KEEFEKTIFAN PENGGUNAAN TEKNIK THINK PAIR SHARE (TPS) DALAM KETERAMPILAN MEMBACA MEMAHAMI BAHASA JERMAN SISWA KELAS X SMA NEGERI 1 KAB. BARRU

Abstract. This research was conducted to obtain data and information about reading skills to understand German students. This research is Quasi Experimental Design. The research population is all students grade X SMA Negeri 1 Kab. Barru consisted of 12 classes totaling 396 students. Sampling in this study uses random sampling with a sample consisting of 2 classes, namely class X IPS 6 as an experimental class with 27 students and class X IPS 4 as a control class with the same number of students, 27 people. The research data was obtained through reading skills tests understanding German. Data were analyzed using t-test with the results showing that t-count 11.89&gt; t-table 2.007 with a significance level of 0.05. Thus this study shows that the use of Think Pair Share techniques is effective in improving reading skills in understanding German students' language.
Performance assessment of a machine-learning-derived digital RF communication classifier

A study is performed to gauge the effectiveness of training a Machine Learning (ML) System for Automatic Modulation Classification (AMC) to accurately identify several diverse digital communication transmission types occurring across the High Frequency (HF) Radio Frequency (RF) spectrum. This study uniquely uses Software Defined Radio (SDR) Power Spectral Density (PSD) waterfall signatures to help classify nine common types of amateur radio digital communication modes. Such an approach provides an alternative to more traditional In-phase/Quadrature (IQ) methods which can require large training sets. LeNet and ResNet Convolutional Neural Network (CNN) models are examined. Training/validation sets sensitivities are examined through Monte Carlo methods. Additionally, performances are examined in terms of confusion matrices as a function of Signal-to-Noise Ratio (SNR).
Network dynamics based multidomain sensor data processing and fusion for multidomain operations

Multidomain sensor data processing and fusion provide reliable ways for situational awareness in multidomain operations and receive great attention in both industry and academia. However, these data processing and fusion are complicated in implementation due to various modalities and high complexity of sensor data. In network dynamics, graph theory is used to represent complex data and extract information, and graph evolution is applied to analyze network dynamics. In this paper, combining the technologies of these two different domains, we propose using network dynamics to process and fuse multidomain sensor data for multidomain operations. First, we propose a graph-theory based framework for multidomain sensor data processing and fusion. Then we apply this general framework to multidomain sensor data processing. Using one-dimensional radio frequency (RF) signal processing, two-dimensional image processing and three-dimensional light detection and ranging (LIDAR) data analytics as examples, we demonstrate that with the proposed method, the same architecture can be used to extract critical features for these three types of sensor data. Furthermore, experiments also show that the proposed method creates higher performance than traditional methods.
Discussion on the Feasibility of Volleyball Description Environment

In the present study, author will aim at the realization of "the volleyball explanation environment". At the first step, the hierarchical structures about “play(action) and skill(means)” are made clear by using state diagrams. The general ball game is the incompleteness information game that the complicated situation is included in. And in volleyball too, game information is recorded by "official record" or "data valley", but much information is abandoned. In the present paper, the hierarchical structures about “play(action) and skill(means)” were described by using PlantUML. Furthermore, state diagrams were described by using “play(action)”. And then, author made the situations of volleyball game clear more by associating "play(action)" and "the position of players" .
A RISC-V Processor Designed For Security

A microprocessor is as secure as its weakest module. Depending on the application, the weakest module may be present in the hardware, micro-architecture, or a vulnerability in the software. For instance in a web-server, the biggest threats occur due to software vulnerabilities and due to information leakage in shared micro-architecture components. On the other hand, in an end-point IoT device, invasive and non-invasive hardware attacks such as Differential Power Analysis (DPA), are arguably the biggest threats. In this paper we highlight some aspects of the development of a secure processor called Shakti-S. The processor is configurable and can cater to vulnerabilities in multiple layers. To protect against memory vulnerabilities that are common in applications, hardware enabled memory protection schemes are implemented. Fine-grained compartment capabilities permit the secure least-privilege software design methodology. In the micro-architecture, shared modules like cache memories are protected by moving target randomization mechanisms which can prevent most variants of cache timing attacks. In the hard-ware, critical information is masked to break correlation with the device’s power consumption, thus hardening the processor against strong side-channel attacks like the Differential Power Analysis.
Good call: the hybrid answer to voice authentication

The benefits of using voice biometrics for speaker recognition in a customer service context are now well-understood. The technology's efficacy and user acceptance has been proven across many implementations involving hundreds of millions of enrolled users.