Reviewerly/exHarmony huggingface dataset:
Financial Literacy and Financial Capability: Interdependence of Concepts and Possibilities to Form Them in a School Course of Mathematics

Financial literacy and financial capacity of schoolchildren should be developed to meet the requirements of the rapidly developing society and increasingly complicated financial system of the Russian Federation. The authors focused on the financial education of schoolchildren who represent a special target group in financial relations. The main research methods were general scientific methods of cognition: systematization of theoretical and practical material, induction, deduction, comparative analysis, and synthesis. The authors defined the concepts of “financial literacy” and “financial capacity” and substantiated their interdependence using a synergistic approach. The authors considered school math course as a special tool for the formation of financial literacy and financial capacity of schoolchildren, explored the possibility of their development among Russian students in grades 7–9 in the course of algebra, stated the main problems, and formulated conclusions and recommendations.
Review on anomalous gait behavior detection using machine learning algorithms

A review on anomalous behavior in crime by other researchers is discussed in this study that focused specifically on the linkage between anomalous behaviors. Next, comprehensive reviews related to gait recognition in utilizing machine learning algorithms for detection and recognition of anomalous behavior is elaborated too. The review begins with the conventional approach of gait recognition that includes feature extraction and classification using PCA, OLS, ANN, and SVM. Further, the review focused on utilization of deep learning namely CNN for anomalous gait behavior detection and transfer learning using pre-trained CNNs such as AlexNet, VGG, and a few more. To the extent of our knowledge, very few studies investigated and explored crime related anomalous behavior based on their gaits, hence this will be the next study that we will explore.
Heterogeneous Computing for Markov Models in Big Data

Many Big Data problems, Markov Model related included, are solved using heterogenous systems: host + parallel programmable accelerator. The current solutions for the accelerator part - for example, GPU used as GPGPU - provide limited accelerations due to some architectural constraints. The paper introduces the use of a programmable parallel accelerator able to perform efficient vector and matrix operations avoiding the limitations of the current systems designed using "of-theshelf" solutions. Our main result is an architecture whose actual performance is a much higher percentage from its peak performance than those of the consecrated accelerators. The performance improvements we offer come from the following two features: the addition of a reduction network at the output of a linear array of cells and an appropriate use of a serial register distributed along the same linear array of cells. Thus, for a n-state Markov Model, instead of a solution with the size in O(n2) and an acceleration in O(n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> =logn), we offer an accelerator with the size in O(n) and the acceleration in O(n).
Adaptive Plot System for Serious Emerging Games based on the Ant Colony Optimization Algorithm

A serious emerging games engine (SEGE) must make explicit the possibility of emergence in a serious game (SG), from the coordinated handling of game plot, adapted to the specific educational context where it is being developed. In previous articles a SEGE based on the ant colony optimization algorithm (ACO) has been proposed, which allows the initial emergence of a SG. In the present work the adaptive plot system (APS) is specified, which allows the emergence of plot in a serious game emerging (SGE), and is based on an ACO that changes the plot in the game, according to the theme that is being given in a smart classroom SaCI (Salón de Clase Inteligente, for its acronym in Spanish),). The APS performs the management of a set of game plot that may be of interest in a context-educational domain, in such a way to adapt the SGE initially conceived to the subject taught in the SaCI, in order to make the appropriate SGE emerge Pedagogical process in progress. Additionally, this paper analyzes the behavior of APS in a case study, showing very encouraging results as SEGE.
Pendeteksian Kerusakan Printer menggunakan Metode Forward Chaining

As technology advances, almost everyone has a printer in their home as a printing aid. but not a few printers that have small or big problems. with this technological advancement, almost all people have personal smarthpones. This research aims to build a moble based system where users can solve printer problems by using applications on their smartphones based on knowledge obtained from experts created by the Forward Chaining method. This expert system can detect nine different types of printers owned by Canon manufacturers with total of 26 Problem and 38 symptomps and has an 80 % of accuracy.
MULTIMEDIA LEARNING FOR WUDHU AND SHOLAT PROCEDURES ANDROID BASED AT TK PERTIWI 01 SERANG

Wudhu is one way to purify oneself from uncleanness and suffering. Performing ablution perfectly in accordance with Islamic Shari'a is the key to receiving prayer. The introduction of religious activities such as ablution and prayer from an early age is considered necessary. Learning ablution and prayer is usually done by parents repeatedly and by example. In one study, 8 out of 10 children aged 5-6 years did not recognize ablution when they were praying. The method of developing multimedia systems by Luther-Sutopo is one of the system development methods used by multimedia application developers. Therefore it will be built an Android operating learning media that uses Adobe Flash technology to display an animated image, motion, and audio in a 2-dimensional form. This learning media will display 2-dimensional objects of ablution movements, namely intentions, washing both feet and prayer after ablution, and prayer movements from beginning to end and added a few daily prayers. The results of this study are in the form of learning applications for ablution and five-time prayer based on Android. In this application using elements of text, images, animations, and sounds to attract and make it easier for children to remember lessons on how to perform ablution and prayer and various kinds of daily prayers.
Pengaman File Video Menggunakan Algoritma Merkle Hellman Knapsack

The issue of security and confidentiality is one important aspect of a message, data or information. In this case it is closely related to how important the message, data, or information is sent and received by parties or people concerned, whether the message, data, or information is still authenticity. At present there are many conveniences in downloading and uploading videos that make videos vulnerable to hijacking, especially if the video is an important and highly confidential video, so an application that is able to encode this important video is needed so that its security can be protected from unauthorized people, except for people who are entitled to. The security technique used by the author in this study uses cryptographic technology. To be able to do well, we need an algorithm for encryption and decryption. The algorithm used here is the Merkle Hellman Algorithm. This Algortman can be used on a video file is something that needs to be considered in maintaining the confidentiality of the data itself, especially if the video file can only be known by certain parties. There are many ways of approach taken to realize the confidentiality of the data starting from security or protection. physical to the form of a mathematical-based algorithm that makes the data illegible. So that the data in it cannot be easily known by unauthorized parties and only the intended video file recipient is able to decipher the video file
Minimal videos: Trade-off between spatial and temporal information in human and machine vision

Objects and their parts can be visually recognized from purely spatial or purely temporal information but the mechanisms integrating space and time are poorly understood. Here we show that visual recognition of objects and actions can be achieved by efficiently combining spatial and motion cues in configurations where each source on its own is insufficient for recognition. This analysis is obtained by identifying minimal videos: these are short and tiny video clips in which objects, parts, and actions can be reliably recognized, but any reduction in either space or time makes them unrecognizable. Human recognition in minimal videos is invariably accompanied by full interpretation of the internal components of the video. State-of-the-art deep convolutional networks for dynamic recognition cannot replicate human behavior in these configurations. The gap between human and machine vision demonstrated here is due to critical mechanisms for full spatiotemporal interpretation that are lacking in current computational models.
A solution to implement Grover quantum computation algorithm using the binary representation of the phase on the FPGA

The system proposed in this paper will be used to implement the Groove quantum computation search algorithm: look in a content addressable memory and find location for a data. Unlike other solutions implemented in FPGA, our solution is trying to achieve the performance of a quantum computing system on resources allocated and search speed.
Visual Tracking Applying Depth Spatiogram and Multi-feature Data

Object tracking, in general, is a promising technology that can be utilized in a wide variety of applications.It is a challenging problem and its difficulties in tracking objects may fail when confronted with challenging scenarios such as similar background color, occlusion, illumination variation, or background clutter.A number of ongoing challenges still remain and an improvement on accuracy can be obtained with additional processing of information.Hence, utilizing depth information can potentially be exploited to boost the performance of traditional object tracking algorithms.Therefore, a large trend in this paper is to integrate depth data with other features in tracking to improve the performance of tracking algorithm and disambiguate occlusions and overcome other challenges such as illumination artifacts.For this, we use the basic idea of many trackers which consists of three main components of the reference model, i.e., object modeling, object detection and localization, and model updating.However, there are major improvements in our system.Our forth component, occlusion handling, utilizes the depth spatiogram of target and occluder to localize the target and occluder.The proposed research develops an efficient and robust way to keep tracking the object throughout video sequences in the presence of significant appearance variations and severe occlusions.The proposed method is evaluated on the Princeton RGBD tracking dataset and the obtained results demonstrate the effectiveness of the proposed method.
Deep learning for modulation and coding rate classification of OFDM

Machine Learning (ML) technologies have been widely used for blind signal classification problem (Modulation Classification) to automatically identify the modulation schemes of Radio Frequency (RF) signal from complex- valued IQ (In-phase Quadrature) samples. Traditional ML methods usually have two stages where the first stage is to manually extract the features of the IQ symbols by subject matter experts and the second stage is to feed the features to an ML algorithm (e.g., a support vector machine) to develop the classifier. The state- of-art technology is to apply Deep Learning (DL) technologies such as Convolutional Neural Network (CNN) or Recurrent Neural Network (RNN) directly to the complex-value IQ symbols to train a multi-class classifier. In this effort we are focused on the modulation and coding rate classification problems for multi-carrier Orthogonal Frequency-Division Multiplexing (OFDM) signals. The generated OFDM data set consists of over 480k instances across four different modulations and three different coding rates which include BPSK + 1=2, BPSK+3=4, QPSK+1=2, QPSK+3=4, QAM16+1=2, QAM16+3=4, QAM64+2=3 and QAM64+3=4. Deep Learning (DL) models can successfully catch the features of OFDM modulations and identify the modulation scheme from the baseband IQ symbols. Four DL models including Residual Neural Network 34(Resnet34), Resnet18, Squeezenet and Long Short-Term Memory (LSTM) trained over the data set can achieve over 94% overall accuracy for signals across 􀀀10dB to 10dB with step size of 4dB. Among them, Squeezenet and LSTM models have much smaller model sizes which can be easily loaded in resource-limited edge computing platforms. To the best of our knowledge, coding rate classification of OFDM signals has not been studied in previous works. Therefore, three different DL models including a single-stage coding rate classifier, a combination of modulation and coding rate classifier, and a two-stage coding rate classifier are developed to identify the coding rate. However, coding rates can only be identified for low-order modulation schemes BPSK and QPSK but not for high-order modulation schemes QAM16 and QAM64. Further investigation is needed to understand the coding rate classification for high-order QAM signals.
A three-term Karatsuba multiplier for a special class of trinomials

In this paper, we continue the study of bit-parallel multiplier using three-term Karatsuba algorithm (KA), recently introduced by Li et al. (VLSI Design 2018). The three-term KA is the simplest variation of the classic Karatsuba algorithm, which multiplies two 3-term polynomials using six scalar multiplications. Based on this observation, Li et al. developed an efficient bit-parallel multiplier scheme for a new special class of irreducible trinomial, namely, xm + xk + 1, m = 3k. The scheme can save about 1/3 logic gates compared with the fastest multiplier so far. However, such a special type of trinomials is quite rare. We consider two more general type of trinomials, where m = 3k + 1 or m = 3k + 2. The corresponding Mastrovito matrices are constructed for different computing parts. It is demonstrated that the space complexity of our proposal matches Li et al. scheme, while its time complexity increases a little. In the end, some comments are derived.
Test and evaluation needs of multi-domain autonomous systems

The paper highlights the need for methods of analytical science for multi-domain autonomy evaluation. Multidomain autonomous systems need to collect large amounts of data to verify, validate, test, and evaluate system operations. For multi-domain and uncertain scenarios, data sampling may not be adequate to fully explore and represent the entire trade space for verification and validation (V&amp;V). However, leveraging methods from test and evaluation (T&amp;E), a hierarchy of analytics can be developed so as to narrow the trade space. Issues in V&amp;V/T&amp;E employ statistics, but could benefit from first-principles physics theoretical analytics, data augmentation, and scenario design. The use of modeling is not new; however, as analytics of artificial intelligence and machine learning (AI/ML) are designed to exploit data; then there are opportunities to allow one domain (e.g., air) support data analytics in another domain (e.g., cyber).
Human-Sizedness As A Principle Of Existance For Literary-Artistic Image

The article is devoted to literary-artistic image in context of its human sized-ness, or its correspondence with natural peculiarities of people who create and perceive it.In this article human sized-ness, characteristic for literary-artistic image, is defined as the principle according to which it exists.Investigations supposing formulation of this principle and justification of its content, precondition the analysis of theoretically formed findings about literary-artistic image and human sized-ness.The discovered statements are creatively processed and concluded in accordance with research goals.The article states as follows: human sized-ness of literary and artistic image must be recognized as ambivalent, as it is established according to two main lines of a person's life: horizontal and vertical, where the first one supposes the realization of natural and social potencies, and the second one is for spiritual potencies; literary and artistic image possesses features, regarded as projections not only of the writer and reader's essences and their virtual interaction, but also of the fragment of fictional literary reality, which this interaction absorbs; human sized-ness of literary and artistic image can be discovered in author-individual and superindividual dimensions because of numerous entwining variants of reader's perception of the author's personality; literary and artistic image, undergoing external influence, actualizes some potencies of human sized-ness, characteristic to it, while remaining the same.The statement of the discussed principle "Genuineness and peculiarities of existence of literary-artistic image are determined by its human sized-ness" is presented in the Conclusion of this article.
Algorithmic Efficiency of Stroke Gesture Recognizers: a Comparative Analysis

Gesture interaction is today recognized as a natural, intuitive way to execute commands of an interactive system. For this purpose, several stroke gesture recognizers become more efficient in recognizing end-user gestures from a training set. Although the rate algorithms propose their rates of return there is a deficiency in knowing which is the most recommended algorithm for its use. In the same way, the experiments known by the most successful algorithms have been carried out under different conditions, resulting in non-comparable results. To better understand their respective algorithmic efficiency, this paper compares the recognition rate, the error rate, and the recognition time of five reference stroke gesture recognition algorithms, i.e., $1, $P, $Q, !FTL, and Penny Pincher, on three diverse gesture sets, i.e., NicIcon, HHReco, and Utopiano Alphabet, in a user-independent scenario. Similar conditions were applied to all algorithms, to be executed under the same characteristics. For the algorithms studied, the method agreed to evaluate the error rate and performance rate, as well as the execution time of each of these algorithms. A software testing environment was developed in JavaScript to perform the comparative analysis. The results of this analysis help recommending a recognizer where it turns out to be the most efficient. !FTL (NLSD) is the best recognition rate and the most efficient algorithm for the HHreco and NicIcon datasets. However, Penny Pincher was the faster algorithm for HHreco datasets. Finally, $1 obtained the best recognition rate for the Utopiano Alphabet dataset.
Mobile Applications for Learning: Exploring Information Technology Undergraduates’ Preference in Malaysia

Mobile devices, mobile applications (apps), smartphones, tabs are all tools used in the proliferation of mobile learning. These devices have been influential in changing how students communicate and learn today hence revolutionizing the 21st-century classroom. A total of 79 Information Technology undergraduates from two higher education institutes participated in this study. Findings revealed that WhatsApp was the most used application for communicating and sharing learning contents with peers and lecturers. Respondents used YouTube and Internet browsers to access alternative learning contents and the least used applications were related to learning management (calendar and cloud storage). Furthermore, results indicated no significant difference between gender and academic year towards their perception and concurrently all students had a positive perception towards using mobile technology for teaching and learning.
Innovative Approaches to Literary Texts (Children Literature on Inclusion)

The research deals with applying to innovative approaches to literary text. Inclusive books for children and ways of working with them at pedagogical faculties are considered. In our research, we will demonstrate the work with such books “Cripple Bunny and his brave mother” by Oksana Drachkovskaya, “Trustees for the Giraffe” by Oksana Luschevska and Yevhenia Haydamaka, “Just because” by Rebecca Elliott, “Magda and her Wind” by Iryna Morykvas, “Planet Willi” by Birta Müller, “Yes! I can!: The girl and her Wheelchair” KendryJ. Barrett, Jacqueline BiuToner, Kler A. Friland, Violet Limey and the trilogy on Pearl of Tuuli Pere. The main heroes of these books are children with disabilities and special educational needs. Narrators mostly are their elder or younger brothers or sisters. The reason of the choosing children’s literature on inclusion is that it is modern important literature, which demonstrates the world of children with disability and highlights such serious topics as decease and death. Its aim is to show that variety makes world wonderful and grate. The introduction of holographic design of vita technologies (calligarm, creative games, the pyramid of hero and author) is considered as well, the application of methods of critical thinking (mind-mapping, swot-analysis, six hats, Bloom’s taxonomy) in the analysis of fiction is substantiated. Potential online resources helping work with literature are examined. In addition, the possibilities of online resources (rebus, comics’ generator, the creating of mind maps, crosswords on different platforms) are determined as important part of the work with text. It has proved that such innovate approaches help to develop creative potential of students, allows analyzing literary text in a new way. Such approaches will be helpful in professional activity of teachers in primary school.
Implementasi Access Control List Pada Mikrotik dalam Mengamankan Koneksi Internet Koperasi Sumber Dana Mutiara

The need for information and internet access at this time is very high. To accept it is wrong only with computer networks as a medium. In a network that requires a network that has been segmented using a Virtual Local Area Network (VLAN), the application of an Access Control List (ACL) is required to be granted access rights for each device in the network. The Access Control List (ACL) can filter the data traffic of a network by controlling whether the packets are passed or issued. A network is built using several different network devices, one of which is a router. A router is a tool that can process different data packet networks (between networks) through a process called routing. lots of companies that produce routers, mikrotik is one of the companies that produce routers. mikrotik is easy to do because it uses Winbox in Gui's view, besides that the hotspot server in it is provided with several management facilities that can be arranged according to network requirements