Reviewerly/exHarmony huggingface dataset:
ИСПОЛЬЗОВАНИЕ РЕСУРСОВ ПРОЕКТНОЙ ТЕХНОЛОГИИ В ПОДГОТОВКЕ ПЕДАГОГОВ В СИСТЕМЕ СРЕДНЕГО ПРОФЕССИОНАЛЬНОГО ОБРАЗОВАНИЯ

Рассматривается необходимость применения проектной технологии в процессе подготовки педагогов в профессиональных образовательных организациях. Дана характеристика проектной технологии, исходя из современных требований, предъявляемых к педагогу, работающему с воспитанниками и учащимися на ступенях дошкольного и начального общего образования, в том числе призванному осуществлять их патриотическое воспитание. Представлено обоснование ресурсов проектной технологии в процессе подготовки будущих педагогов. Приводится пример проекта, разработанного будущими педагогами для воспитанников дошкольных образовательных организаций с целью их патриотического воспитания. The article deals with the issue of using project technologies in the process of training teachers in the system of secondary vocational education. Contemporary scientific achievements permit us to modernize project technologies significantly compared to the beginning of the last century and to enhance their relevance for the training of future teachers. It is necessary that these technologies should be used according to the contemporary requirements of the state and society to the pre-school and primary school teachers. Based on these requirements, using project technologies is aimed to overcome passivity of future teachers in their education which determines further results of their professional activity, to increase future teachers’ motivation to use new technologies for improving the quality of education at the pre-school and primary levels. It also helps to improve the quality of future teachers’ educational content in terms of patriotic education of the primary school and preschool children. The article presents the concepts of “vocational training”, “project”, “projectbased learning”, “project technologies”. It reveals the importance of project technologies as the specific universal tool affecting directly both content and organization of future teachers’ training and providing its effectiveness. This approach draws the attention of the scientific and pedagogical community to the importance of using project technologies in terms of their core resources. The article presents the justification of the project technologies resources (activity orientated, productive, research, social and others) for their most effective use in the educational content. For illustrative purposes the author provides the description of the project made by future teachers for the pre-school children’s patriotic education.
A Flexible Replay Delay Control Method for GNSS Direct Meaconing Signal

In this paper, we introduce a flexible delay control method for the GNSS direct meaconing signal. Since GNSS has been playing an important role in human life, we need to pay attention to its security issues, especially spoofing attacks. In order to explore the corresponding anti-spoofing techniques, we should know more about spoofing methods so that we can study the characteristics of spoofing signals. As far as an encrypted GNSS signal is concerned, only the direct meaconer can generate the corresponding spoofing signal. In detail, the meaconer receives authentic signals from different directions and delays them with different delays, respectively. However, the delay control method has not yet been public, which restricts researchers to explore more efficient anti-spoofing methods. To this end, we introduce a flexible delay control method for meaconer based on the integer and fractional delay filters. In detail, the integer filter can delay the signal with an integer delay that is an integer multiple of sampling period, and the fractional filter can delay the signal by a fraction delay. We implement the fractional filter using the Farrow structure so that we only need to adjust one parameter in the filter if the replay delay changes. As a consequence, the delay control method is flexible and easy to implement on a hardware platform. We verify the introduced method by carrying out meaconing attacks against both the GNSS-SDR receiver and the GPS hardware receiver of our lab.
Deteksi Serangan Distributed Denia of Services (DDOS) Berbasis HTTP Menggunakan Metode Fuzzy Sugeno

Distributed Denial of Services (DDOS) is a type of attack that exploits the web. This attack causes the server to go down and a system error. Thus, early detection of DDOS attacks is fundamental. The purpose of this paper is to develop applications that are capable of detecting HTTP-based DDOS attacks. This paper uses the sugeno fuzzy method for a systematic approach. From several studies that have been conducted, the researchers identified that the optimal input variables included the number of users, number of packages, number of lengths / users, and length of packages. Data processing used MATLAB software. The validity of the test uses the formula for the level of accuracy as in equation (3), resulting in an application that is able to detect HTTP-based DDOS attacks using sugeno fuzzy method with an accuracy rate of up to 90%.
EXPLORING DACIAN CULTURAL HERITAGE WITH dARcit AUGMENTED REALITY APPLICATION

This paper is focused on highlighting the advantages of using modern augmented reality applications to support the widespread dissemination of Cultural Heritage assets. This kind of applications have the potential to improve the user experience when they are visualizing a hard cover printed book or catalogue. The main advantage of this solution is to allow users to use their personal smartphones and tablets to access additional interactive content related to main subject of tangible books. Using the proposed solution described within the article any printed material can become interactive using multimedia elements such as: audio files, 3D models, images, videos (2D, 3D, 360°), 3D text or any other form of digital content. The application adds multimedia information on top of the printed information increasing the degree of understanding of the information presented in the form of a book / catalogue, regardless of the time in which it was written and published.
Context Pattern Based Agricultural Named Entity Recognition

Named entity recognition (NER) play a vital role in various application of Natural Language processing.Although a significant work has been done in general and biomedical domain NER, but agriculture domain has been ignored for a long time.Agriculture entity includes name of crops, crop diseases, fertilizers etc. Due to the inapplicability of conventional features which has been used for identifying general named entities, recognizing and extracting the agricultural entities become a rigorous and challenging task.As NER in agriculture domain has not been yet explored a lot, thus building up a NER system for agriculture domain is very recent and vital work.This paper proposes a novel context-based approach to develop a NER system for agriculture domain.The proposed approach employs the context pattern for extracting the required entity of interest.The experiment is carried out in two different genres 1) Word Context Pattern 2) POS context pattern.In word context pattern, merely the cooccurring word tokens corresponding to the required entity is considered.While in Part of Speech (POS) rather than considering the co-occurring word tokens, their POS structure is plied.We have proposed seven part of speech patterns which are most likely to comprise all the instances of required entity of interest.The remarkable point is that the proposed POS patterns have not only device the known agricultural entities but have also extracted out 55 hidden entities from the data set.To boost up the performance of the NER system semantic similarity module has also been exercised.The proposed approach attains an accuracy of 70.45 % and recall of 91.3% which is appreciable as the preparatory work.
Multi-Label Learning With Hidden Labels

In multi-label learning, each object is represented by a single instance and associated with multiple labels simultaneously. Existing multi-label learning approaches mainly construct classification models with a fixed set of target labels ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">observed labels</i> ). However, in the big data era, it is difficult to provide a fully complete label set for a data set. In some real applications, there are multiple labels <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hidden</i> in the data set, especially for those large-scale data sets. In this paper, a novel approach named MLLHL is proposed to not only discover the hidden labels in the training data but also predict these <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hidden labels</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">observed labels</i> for unseen examples simultaneously. We assume that the observed labels are just a subset of labels which are selected from the full label set, and the rest ones are omitted by the annotators during the labeling stage. Extensive experiments show the competitive performance of MLLHL against other state-of-the-art multi-label learning approaches.
Arsitektur Sistem Informasi Sekolah

The design of school information systems enterprise architecture is carried out to find detailed information about school activities based on government regulatory standards. So that the existing information system in the school business is in accordance with the existing standards of the government and there will be no errors in school activities later, a research is carried out that implements TOGAF ADM as a method in building the architecture of school information systems enterprise. Then the results obtained by business architecture include PSB (Acceptance of New Students), PA (Academic Process), PS (Release of Students), MTU (Management of Administration), MSP (Management of Facilities and Infrastructure), LAB (Laboratory), and the acquisition of architecture data, application architecture and technology architecture. So it can be concluded that the TOGAF ADM Method was successfully implemented in the School Information System Architecture and the School Information System Architecture can be used as a guide in the development and development of information systems in terms of data and information management in schools.
Contribution of multispectral remote sensing to mining exploration in the Rehamna Massif, Moroccan Meseta

The Western Moroccan Meseta contains mining sites in operation for several decades and others in development. The Rehamna Massif belonging to this, is the subject of this study. The present study reveals new results on the mineralization in this massif. It is based on the synergy of field investigation data and ASTER image analysis (L1T) covering this massif. Through spectral processing, namely the calculation of the band ratios, ACP and MNF, applied to the nine VNIR and SWIR bands of this image, it was possible to reveal the distribution of hydrothermal alteration minerals in the study area. The conjuncture of these data allowed us to select geological targets likely to be of potential mining interest in the massif.
Business Games as a Teaching Strategy for Delivering a Practice-Oriented Course in Mathematics at Agricultural University

The development of markets for scientific and technological initiatives in modern Russia requires the transformation of educational processes.Highly qualified specialists with "hard skills" and "soft skills" are more in demand.The application of practice-oriented approaches to educational activities ensures the development of these competencies.Mathematics studies are not limited by a specific discipline.Some aspects of mathematics are involved in other profession-related disciplines, too.The practical activities of undergraduates at agricultural universities include a lot of experimental work and analysis of the results.The teachers can simulate this situation in the educational process with the help of business games, which allows the increase of students' proactive behavior and motivation in the educational process and identification of the talented youth.With the purpose of improvement of the effectiveness of the educational process, several disciplines should be joined together in the business game.For agricultural universities, the most acceptable example of discipline convergence is a combination of mathematics, genetics and biology.The authors found out that the use of business games in the educational process has improved the quality of knowledge of students in the disciplines up to 70-80%.The average performance of students in mathematics was 70%, which is 5% higher than before the introduction of this teaching strategy in the educational process.
Mixed Noise Parameter Estimation Based on Variance Stable Transform

The ultimate goal of image denoising from video is to improve the given image, which can reduce noise interference to ensure image quality.Through denoising technology, image quality can have effectively optimized, signal-to-noise ratio can have increased, and the original mage information can have better reflected.As an important preprocessing method, people have made extensive research on image denoising algorithm.Video denoising needs to take into account the various level of noise.Therefore, the estimation of noise parameters is particularly important.This paper presents a noise estimation method based on variance stability transformation, which estimates the parameters of variance stability transformation by minimizing the noise distribution peak, and improves the parameter accuracy of mixed peak estimation by comparing and analyzing the changes of parameters.The experimental results show that the new algorithm of noise estimation has achieved good effects, which are making the field of video denoising more extensive.
Обгрунтування показника вибору оптимального алгоритму виділення фону у відеопослідовностях з камер відеоспостереження відомчих систем відео спостереження

The background subtraction is an important stage in the process of detecting moving objects in video sequences derived from stationary cameras of video surveillance systems (VSS cameras). A variety of approaches to addressing the background selection problem in video sequences from stationary cameras of video surveillance systems has created the need for research on the choice of optimal algorithms.In this paper, we described the problem factors that complicate the background allocation process and described the basic background subtraction algorithms classifications.After analyzing the location of VSS cameras for certain objects within the Information and Telecommunication Systems of the State Border Guard Service and their inspection sectors, we have identified the features of the use of cameras from these systems.We researched the most common algorithms of background subtraction in video sequences, methods of comparative analysis and methodes for selecting optimal background subtraction algorithms in video sequences from stationary VSS cameras.We developed an improved efficiency index for the choice optimal algorithms for the background subtraction in video sequences derived from stationary cameras of video surveillance systems оn the basis method proposed Sobral Andrews and Vacavant Antoine in the "Comprehensive review of subtraction algorithms evaluated using synthetic and real video".The essence of the improved method is that we propose to calculate the overall performance of the background subtraction algorithm using Matthews correlation coefficient, because this coefficient takes into account all possible variants of the matrix of algorithm responses (TP, TN, FP, FN).The proposed method was tested by calculating the results of the experimental study in the "A comprehensive review of the subtraction algorithms evaluated using synthetic and real videos". As a result, we have developed the index of efficiency of an algorithm of background subtraction, that differs from that offered gathered Sobral Andrews and Vacavant Antoine (FSD), because it takes into account all options matrix classifier responses, and therefore is more accurate than the FSD.
Monotonicity of the system function of a SISO FRI system with neutrality and ordering property preserving fuzzy implications

The monotonicity of the system function of a fuzzy relational inference (FRI) system is one of the most important issues that need attention. The unavailability of monotonicity of the system function of an FRI system is not desirable in many practical settings. Works existing in the literature have dealt with monotonicity of the system function of an FRI system where fuzzy implications have been widely used and those fuzzy implications are known to come from a residuated lattice structure. Moreover, there are very few studies where monotonicity has been studied under a non-residuated lattice structure. Building on our recent work on monotonicity under a non-residuated setting, in this work, we ensure that the system function of a certain type of FRI system with a Single-Input Single-Output (SISO) implicative rule base and ordering property preserving fuzzy implications is monotonic. Towards doing this, we represent the monotone fuzzy rule base by a fuzzy relation that involves fuzzy implications which satisfy the so-called neutrality property and ordering property, simultaneously. It should be highlighted that this work generalizes the class of fuzzy implications that can be employed in an FRI system without modifying the rule base to ensure the monotonic nature of the system function, giving more choices to the practitioners.
Neural Network Backpropagation Identification of Jakarta Islamic Index (JII) Stock Price Patterns

Jakarta Islamic Index (JII) is an organization engaged in the economy with the aim to pay attention to stock movements every day. With the JII, people who do not understand about shares and their movements, will be easy to know and understand the movement of shares that occur at certain times. The problem in this research is that many investors are unable to predict the rise and fall of stock prices. The prediction process can be done with a backpropagation algorithm. The algorithm is a concept of computer science which is widely used in the case of analysis, prediction and pattern determination. The process starts from the analysis of the variables used namely interest rates, exchange rates, inflation rates and stock prices that occurred in the previous period. The variables used are continued in the formation of network patterns and continued in the process of training and testing in order to produce the best network patterns so that they are used as a process of identifying JII stock price movements. The results obtained in the form of the value of stock price movements with an error rate based on the MSE value of 11.85% so that this study provides information in the form of knowledge for making a decision. The purpose of the research is used as input for investors in identifying share prices. In the end, the benefits felt from the results of this study, investors can make an initial estimate before investing in JII.
Learning with Drift Detection based on k Time Sub-concept Windows

Concept drift detection has attracted much interest lately, due to the fact that a massive amount of streaming data are continuously being generated. Traditional concept drift detection methods, based on the monitoring performance of a base learner over instances from a data stream's whole time window, are not sensitive enough to sub-concept drifts and discover them late or not at all. This is because when aggregated together, the sub- concepts that form a concept are not carefully described. To solve this problem, we propose the kTSW based method that divides instances from a data stream's whole time window into \pmbk subconcept windows, and then builds a drift monitor for instances from each sub window. Once a sub window's instances have experienced a concept drift, we update the learned model. Two real data sets are used to verify the validity of our method in data stream classification. Experimental results show that our method obtained higher accuracy and recall than methods based on the whole time window.
ANALYZING CHALLENGES IN GRAMMATICAL KNOWLEDGE FOR EFL STUDENTS: Descriptive Quantitative Study

This research aimed to find out what challenges were faced by EFL students at the English Department Muhammadiyah University of Makassar in their grammatical knowledge. This research used descriptive quantitative. The population of this research was the fourth semester of the English Department Muhammadiyah University of Makassar. The sample or the subject of this research was 50 students taken by accidental sampling technique. The researcher used the questionnaire as the instrument of this research. The result showed that challenges were mostly found by the students in developing their grammatical knowledge were: do not know how to organize the sentences to be a good paragraph, lack of self-confident, lack of vocabularies, lack of tenses and the biggest challenges were learning environment was too crowded, limited of time and lack of facilities.
IDENTIFICATION OF DRAINAGE SYSTEMS CAPACITY USING EPA-SWMM 5.1 VERSION MODELING IN GUNUNG PANGILUN OF PADANG CITY

Floods have often occurred in the city of Padang, PALAPA Metropolitan Urban Area in recent years, this is generally caused by high rainfall and poor drainage capabilities. NVivo software is utilized to analyze the online news which reported floods occurrence. Based on the news collected from 2009–2018, it was found that Gunung Pangilun Village, Padang Utara Subdistrict was often flooded when it rained for more than 3 hours. This area is a densely populated area (1,000 people / km2). The cause of inundation in this area is that drainage is not able to accommodate water and high rainfall intensity with the parent river in the Batang Kuranji watershed. The flooding that occurred in this area caused several schools, offices and hospitals to be flooded, a number of houses and a number of points on the local road were flooded. Therefore, it is necessary to know the large drainage capacity that is able to accommodate the amount of runoff discharge when the rain occurs using the 5-year return EPA SWMM software modeling