Reviewerly/exHarmony huggingface dataset:
Design and Implementation of a Timing and Calculating Rings System Based on RFID and WSN

This paper proposes a multiple participants based on RFID and WSN middle-long-distance timing problem. The current preliminary 2 nodes in the 400 - meter runway standard setting, cadets read RFID tags to carry through time, with the aid of WSN network, data statistics 3000 meters total has 16. By recording student movement time of each point and the artificial timing results than, the error of the 800 m and 3000 m between 3 to 6 seconds, a fitness test system based on RFID and WSN scheme is used in the sport automatic timing is feasible.
Improvised Spam Detection in Twitter Data Using Lightweight Detectors and Classifiers

Receiving spam messages is one of the most serious issues in social media, especially in Twitter, which is a widely used platform to reflect the opinions and emotions of an individual publicly as well as focused to a specific group of members with similar thoughts or discussion topic. In such focused discussion groups, getting spam message through social media sites is the most annoying issue. In this paper, a system is developed to detect spam tweets by using four lightweight detectors, namely blacklist domain detector, near duplicate detector, reliable ham detector, and multiclass detector. The detected tweets are then classified using ensemble classifiers such as naïve Bayes, logistic regression, and random forest. Voting method is applied to decide the labels for the tweets obtained after classification process. The proposed system has achieved an accuracy of 79% to detect spam tweets with the help of naïve Bayes classifier method and the value seems to be optimizing further with the availability of more sample data.
Population-Based Novelty Searches Can Converge

Novelty search is a powerful tool for finding sets of complex objects in complicated, open-ended spaces. Recent empirical analysis on a simplified version of novelty search makes it clear that novelty search happens at the level of the archive space, not the individual point space. The sparseness measure and archive update criterion create a process that is driven by a clear pair of objectives: spread out to cover the space, while trying to remain as efficiently packed as possible driving these simplified variants to converge to an
Information of System Monitoring by Network Oparation Center

Network Operation Central (NOC), an Enterprise Service Division which functions to carry out monitoring and supervision activities of Telkom network equipment located at Plaza Indonesia. Customer satisfaction is the basis and goal that is always hoped for by customers, by carrying out maintenance activities of network devices, and carrying out solutions when problems occur in customers are expected to be an efficient and effective service quality standard. This study wants to know that the construction of a monitoring system for NOC work activities can improve service quality. The quality of this system can be measured using the ISO9126 model, by adapting four characteristics of software quality: functionality, reliability, usability, and efficiency. The system development model uses the Rapid Application Development (RAD) and Joint Application Development (JAD) models. Researchers will analyze and design the system using the Unified Model Language (UML), then by coding with PHP programming and MySQL databases, and data collection using a questionnaire, and system testing using the Blackbox Testing model. Based on testing using ISO 9126 the results are functionality (80%), reliability (79%), usability 86%), and efficiency (79%). Overall the result was 81% (good).
PREPARING THE FUTURE EDUCATOR TO THE CREATION OF AUGMENTED REALITY EXCURSIONS IN LOCAL EDUCATIONAL ENVIRONMENTS

The article highlights the peculiarities of future teachers'&nbsp;preparation for the organization of augmented reality virtual excursions in educational institutions. The pedagogical conditions fordevelopment and conductingsuch excursions of augmented reality in local educational environments are found out on the basis of BYOD concept. The differences, advantages and disadvantages of virtual, augmented and mixed reality excursions in the educational process of pedagogical institutions are also analysed. The ways of realization of the offered approach are presented, in particular creation of the routes of excursions in education by means of QR codes, which extends the boundaries of conducting excursions in space and in time, makes this form of training more flexible and systematic. The stages and peculiarities of creation the excursion routes in local environments of educational institutions were grounded, the method of diagnostics of certain aspects of students' knowledge about the conditions of the creation of virtual excursions in local educational environments is presented. Attention is paid to the importance of future teachers' media education as theywill design the educational environmentsincluding modern informative and pedagogical innovations, and the logic of the evolutionary change of computerized textbooks and online educational resources for mobile learning is proved.
Algorithm Of The Electronic Digital Subscript On The Basis Of The Composition Of Computing Complexities

In article the new algorithm of a digital signature in composition of the existing difficulties is developed: discrete logarithming in a final field, decomposition of rather large natural number on simple multipliers, additions of points with rational coordinates of an elliptic curve. On the basis of a combination of difficulties of discrete logarithming on a final field with the characteristic of large number, decomposition of rather large odd number on simple multipliers and additions of points of an elliptic curve develops algorithm of a digital signature for formation. The conventional scheme (model) of a digital signature covers three processes: generation of keys of EDS; formation of EDS; check (authenticity confirmation) of EDS. The idea of a design of the offered algorithm allows modifying and increasing crypto stability with addition to other computing difficulties. It is intended for use in systems of information processing of different function during forming and confirmation of authenticity of digital signature.
Monte Carlo Optimization of a Combined Image Quality Assessment for Compressed Images Evaluation

In image processing, using compression is very important in various applications, especially those using data quantities in transmission and storing. This importance becomes most required with the evolution of image quantities and the big data systems explosion. The image compression allows reducing the required binary volume of image data by encoding the image for transmission goal or database saving. The principal problem with image compression when reducing its size is the degradation that enters the image. This degradation can affect the quality of use of the compressed image. To evaluate and qualify this quality, we investigate the use of textural combined image quality metrics (TCQ) based on the fusion of full reference structural, textural, and edge evaluation metrics. To optimize this metric, we use the Monte Carlo optimization method. This approach allows us to qualify our compressed images and propose the best metric that evaluates compressed images according to several textural quality aspects.
A Hardware-Efficient Elliptic Curve Cryptographic Architecture over GF (p)

This paper proposes a hardware-efficient elliptic curve cryptography (ECC) architecture over GF(p), which uses adders to achieve scalar multiplication (SM) through hardware-reuse method. In terms of algorithm, the improvement of the interleaved modular multiplication (IMM) algorithm and the binary modular inverse (BMI) algorithm needs two adders. In addition to the adder, the data register is another optimize target. The design compiler is synthesized on 0.13 µm CMOS ASIC platform. The time range of performing scalar multiplication over 160, 192, 224, and 256 field orders under 150 MHz frequency is 1.99–3.17 ms. Moreover, the gate area required for different field orders in this design is in the range of 35.65k–59.14k, with 50%–91% hardware resource less than other processors.
Do Cryptocurrencies have a Future in Emerging Markets? Evidence from Mauritius

For the last two decades, we have witnessed major changes in technological advances. Most if not all individuals worldwide use technological tools to ease their lives. Mobile devices and computers are being used daily and through such devices, one can perform its investment or banking activities arround the clock. The purpose of this paper is to assess whether cryptocurrencies will have a future in emerging markets and especially in Mauritius. Mauritius is an island situated in the Indian Ocean and has a population of approximately one million two hundred citizens and ninety-one as at January 2019. The aim of the study is to investigate the factors that could lead to the adoption of cryptocurrencies in Mauritius. An online questionnaire was prepared and sent to 100 respondents and 71 were deemed as valid for the analysis. Our empirical findings showed that students and employed individuals could be the potential users of cryptocurrencies. Undoubtedly, the use of cryptocurrencies is strongly influenced by the regulations to be put in place. Recommendations have been made in view to assess the possible future of cryptocurrency in Mauritius.
Single Run Action Detector over Video Stream - A Privacy Preserving Approach

This paper takes initial strides at designing and evaluating a vision-based system for privacy ensured activity monitoring. The proposed technology utilizing Artificial Intelligence (AI)-empowered proactive systems offering continuous monitoring, behavioral analysis, and modeling of human activities. To this end, this paper presents Single Run Action Detector (S-RAD) which is a real-time privacy-preserving action detector that performs end-to-end action localization and classification. It is based on Faster-RCNN combined with temporal shift modeling and segment based sampling to capture the human actions. Results on UCF-Sports and UR Fall dataset present comparable accuracy to State-of-the-Art approaches with significantly lower model size and computation demand and the ability for real-time execution on edge embedded device (e.g. Nvidia Jetson Xavier).
Musicals Repertoires Enter the Classroom of Music Education in Normal Universities

The author analyzes the current situation of music education and singing classroom teaching in normal universities, and through the study of musicals repertoire, improve teaching ideas, improve teaching quality, enhance students' comprehensive quality, and enhance students' competitiveness in social practice scenes after graduation. It is hoped that through gradual research, some suitable musicals will become an effective means of implementing vocal music education in normal universities.
Neural network particle picking and denoising in cryoEM with <i>Topaz</i>

Single particle cryoEM projects are often hampered by low SNR particle views, which are missed by most particle pickers or severely de-prioritized causing junk to be preferentially picked.Moreover, for non-globular, small, asymmetric, and aggregated proteins, picking and centering such particles becomes critical.To solve these issues and more, we present Topaz particle picking using a novel positive-unlabelled framework and Topaz-Denoise using the Noise2Noise framework.We show that Topaz and Topaz-Denoise significantly increase the number of real particles picked, enable conventionally difficult projects, significantly decrease classification bias, and increase collection efficiency.We show the first in-depth analysis of pre-trained 2D and 3D denoising models for cryoEM and cryoET, which remove the characteristic sheets of noise in cryoEM micrographs of proteins and cryoET cellular tomograms.In the past few months, Topaz has been used by several labs around the world to enable and optimize single particle SARS-CoV2 projects.These recent projects and more will be highlighted to show the unique and timely power of Topaz.We will also highlight Topaz integration into the most popular cryoEM suites: Relion, CryoSPARC, Scipion, and Appion.
Optimal Control of Mathematical Models on The Dynamics Spread of Drug Abuse

This article examines the optimal control of a mathematical model of the spread of drug abuse. This model consists of five population classes, namely susceptible to using drugs (S), light-grade drugs (A), heavy-grade drugs (H), medicated drugs (T), and Recovery from drugs (R). The system is solved using the Pontryagin minimum principle and numerically by the forward-backward sweep method. Numerical simulations of the optimal problem show that with the implementation of anti-drug campaigns and strengthening of self-psychology through counseling, the spread of drug abuse can be eradicated more quickly. The implementation of campaigns and strengthening of self-psychology through large amounts of counseling needs to be done from the beginning then the proportion can be reduced until a certain time does not need to be given anymore. The use of control in the form of strengthening efforts to self-psychology through counseling means that it needs to be done in a longer time to prevent the spread of drug abuse.
matteo-brv @ DaDoEval: An SVM-based Approach for Automatic Document Dating

This paper describes our contribution to the EVALITA 2020 shared task DaDoEval – Dating Document Evaluation. The solution we present is based on a linear multi-class Support Vector Machine classifier trained on a combination of character and word n-grams, as well as number of word tokens per document. Despite its simplicity, the system ranked first both in the coarse-grained classification task on same-genre data and in the one on cross-genre data, achieving a macro-average F1 score of 0.934 and 0.413, respectively. The system implementation is available at https://github.com/matteobrv/DaDoEval.
A comprehensive swarming intelligent method for optimizing deep learning-based object detection by unmanned ground vehicles

Unmanned ground vehicles (UGVs) are an important research application of artificial intelligence. In particular, the deep learning-based object detection method is widely used in UGV-based environmental perception. Good experimental results are achieved by the deep learning-based object detection method Faster region-based convolutional neural network (Faster R-CNN). However, the exploration space of the region proposal network (RPN) is restricted by its expression. In our paper, a boosted RPN (BRPN) with three improvements is developed to solve this problem. First, a novel enhanced pooling network is designed in this paper. Therefore, the BRPN can adapt to objects with different shapes. Second, the expression of BRPN loss function is improved to learn the negative samples. Furthermore, the grey wolf optimizer (GWO) is used to optimize the parameters of the improved BRPN loss function. Thereafter, the performance of the BRPN loss function is promoted. Third, a novel GA-SVM classifier is applied to strengthen the classification capacity. The PASCAL VOC 2007, VOC 2012 and KITTI datasets are used to test the BRPN. Consequently, excellent experimental results are obtained by our deep learning-based object detection method.
METHOD OF FORMING AN EFFECTIVE TEAM OF EDUCATIONAL PROFESSIONAL PROJECTS

Project management methodology is widely used in various aspects of educational activities, including in the field of adult education. In-service training projects implemented by higher education institutions in the field of adult education, mainly at public expense, are limited, on the one hand, in terms of implementation, which leads to the impossibility of increasing project implementation time, then in the amount of funding regulated by relevant provisions and resolutions on the organization of professional training (advanced training) of specialists, and on the other hand, the internal regulations and rules of educational institutions on the organization of training and implementation of educational projects in the field of higher education, aimed at working with students. At the same time, the implementation of such projects is subject to increased requirements for their quality. Under such conditions, the implementation of educational projects of professional development is quite difficult. Teams of educational projects of advanced training are formed mainly of persons selected from among the internal employees of the educational institution, who are able to work with an adult audience. To form such teams, it is necessary to take into account the peculiarities of adult learning, the peculiarities of educational projects of professional development and the peculiarities of the teams of such projects. Accordingly, the management of such teams is associated with certain personnel risks that may affect the success of the project. In turn, working with teams whose members have a high creative potential requires effective management methods, one of which is the process of forming a single, coherent team of like-minded people who can effectively achieve the project goal. A method of forming teams of educational projects of advanced training, obtained as a result of cross-evaluation of qualities (creativity) of team members of such projects, taking into account their personnel risks and "degrees of trust", is proposed. It is concluded that this method allows the head of the educational project to increase the efficiency of decision-making on team building or planning of executors for the educational project of professional development, by selecting applicants with the highest "degrees of trust".
STUDENTS’ RESPONSE TOWARD THE IMPLEMENTATION OF MINDOMO IN WRITING DESCRIPTIVE TEXT AT THE SEVENTH GRADE THE STUDENTS IN CIMAHI

This study aims to describe students' responses toward the implementation of Mindomo in writing description text at seventh-grade students in Cimahi. This study used descriptive qualitative methods. The participant of the study is 33 students’ junior high school in Cimahi. The result of this study showed that the implementation of Mindomo in teaching writing descriptive text gave positive responses to 81,80%. This positive response was shown with the enthusiasm of students during the learning process. Aspects of attention get the largest average score of around 24.54, which shows students are more interested in the learning process of writing using the Mindomo application. Besides, the aspect of confidence and satisfaction get the lowest score 12, it can be seen that the students are lack of confidence and have a fear of writing.
Geochemical Characterization Of Pottery Shards Unearthed From Kampung Baru Archaeological Site, Kedah, Malaysia

Candi Kampung Baru is situated in the Kampung Baru Archaeological Site, and it is one of the temple sites that used bricks as the main construction material. Based on the Global Positioning System, Candi Kampung Baru is located at N 05.58215°, E 100. 38004°. Apart from bricks, granite stones were also used as the pillar base of the construction’s structure. This study is an analytical approach on the pottery properties of clays discovered at the Kampung Baru Archaeological Site. X-ray diffraction (XRD), X-ray fluorescence (XRF) and physical analysis have been performed on these potsherds. 15 pottery shard samples were analysed to determine the chemical and mineralogical characteristics of the pottery shards. The results indicate a local provenance of these samples. The mineral content in the pottery samples also indicate the presence of minerals, such as quartz, illite, datolite and microcline. Furthermore, the physical analysis conducted uncovered a variety of motifs that adorned the earthenware, such as lines, nets, square and floral motifs. The mineral content and physical observation of the pottery shards indicate that the open burning technique was used to produce these pottery shards due to the presence of illite mineral in the pottery shards. The mineral content (namely illite) also shows that the samples were baked at a temperature between 650°C and 750°C. The content of the major and trace elements also proves that these potteries were produced from the same source and it is proposed that local raw materials were used in the production of the potteries, from which the nearest source that could be detected is at the Muda River basin. Moreover, the involvement of the local community in producing the potteries should not be refuted, as this proves that the knowledge of producing pottery by the local community had already started since the evolution of the Neolithic culture at the Muda River basin since 4000 to 5000 years ago.
Role-Based Embedded Domain-Specific Language for Collaborative Multi-Agent Systems through Blockchain Technology

Multi-agent systems have evolved with their complexities over the past few decades. To create multi-agent systems, developers should understand the design, analysis, and implementation together. Agent-oriented software engineering applies best practices through mainly software agents with abstraction levels in the multi-agent systems. However, abstraction levels take a considerable amount of time due to the design complexity and adversity of the analysis phase before implementing them. Moreover, trust and security of multi-agent systems have never been detailed in the design and analysis phase even though the implementation of trust and security on the tamper-proof data are necessary for developers. Nonetheless, object-oriented programming is the right way to do it, when implementing complex software agents, one of the major problems is that the object-oriented programming approach still has a complex process-interaction and a burden of event-goal combination to represent actions by multi-agents. Designated roles with their relationships, invariants, and constraints of roles can be constructed based on blockchain contracts between agents. Furthermore, in the case of new agents who participate in an agent network, decentralization and transparency are two key parameters, which agents can exchange trusted information and reach a consensus aspect of roles. This study will take the software agent development as a whole with analysis, design, and development with role-object pattern in terms of smart contract applications. In this paper, we aim to propose a role-based domain-specific language that enables smart contracts which can be used in agent-oriented frameworks. Furthermore, we would like to refer to methodology, results of the research, and case study to enlighten readers in a better way. Finally, we summarize findings and highlight the main research points by inferencing in the conclusion section.