Reviewerly/exHarmony huggingface dataset:
Um acelerador em hardware para a cifra ChaCha20

ABSTRACTCurrent computer systems use encryption extensively, for example,in instant messaging, virtual private network protocols, andwebsites in general. However, employing encryption in a systemcan be computationally costly, resulting in lower throughput orhigher latencies. One strategy to mitigate the costs imposed by theapplication of cryptography is the use of accelerators dedicatedto the execution of this task. In this context, this paper presentsthe development of an encryption accelerator for the ChaCha20stream cipher. The accelerator was prototyped on two FPGA SoCplatforms, achieving a normalized speedup of 3.49 times comparedto the software implementation.
Multi-branch Deep Neural Model for Natural Language-Based Vehicle Retrieval

Natural language interfaces (NLIs) have seen tremendous popularity in recent times. The utility of natural language descriptions for identifying vehicles in city-scale smart traffic systems is an emerging problem that has received significant research interest. NL-based vehicle identification/retrieval can significantly improve existing systems’ usability and user-friendliness. In this paper, the problem of NL-based vehicle retrieval is explored, which focuses on the retrieval/identification of a unique vehicle from a single-view video given the vehicle’s natural language description. Natural language descriptions are leveraged to identify a specific target vehicle based on its visual features and environmental features such as trajectory and neighbours. We propose a multi-branch model that learns the target vehicle’s visual features, environmental features, and direction and uses the concatenated feature vector to calculate a similarity score by comparing it with the feature vector of the given natural language description, thus identifying the vehicle of interest. The Cityflow-NL dataset was used for the purpose of training/validation, and the performance was measured using MRR (Mean Reciprocal Rank). The proposed model achieved a standardised MRR score of 0.15, which is on par with state-of-the-art models.
PERANCANGAN SISTEM INFORMASI KANTOR CAMAT SIPOHOLON KABUPATEN TAPANULI UTARA BERBASIS WEB

Technology is growing along with the increasing need to enter the world of globalization, we recognize increasingly advanced technology to make it easier to carry out various activities in life. The sub-district is a government organization consisting of several villages, with an information system in the Sipoholon sub-district will greatly assist the sub-district government in receiving or providing information to the public and to higher government agencies in a short time. Based on the existing problem, how to make a website information system at the Sipoholon sub-district office. Thus, a system is needed that can facilitate the process of efficient data information for sub-district employees in updating data without having to wait for data change reports about the Sipoholon sub-district office, make it easier for sub-district employees to process data and report news data, village announcements so that they can affect the optimization of the work process of sub-district employees.
A Random Forest-based No-Reference Quality Metric for UGC Videos

The images and videos randomly captured by people for sharing in social media or their own use are commonly termed as the user generated content. With the growing popularity of various social media and streaming platforms along with the availability of low-cost portable devices, the amount of such user generated content is exponentially increasing. Visual quality assessment of such user-generated contents is necessary for various purpose such as estimating how the distortions induced during media transmission effects the visual quality of the non-professionally captured image or video, the social media platforms to estimate quality of a media before it gets posted, assessing quality to evaluate performance of a handheld camera or mobile phone, etc. This is a very challenging task due to the fact that the user generated content significantly suffers from multiple artifacts and distortions during both the capturing and transmission pipeline stage that eventually hinder the visual quality. This work mostly deals with the artifacts induced during video capturing stage, and subsequently, use them for estimating visual quality. A random forest-based no-reference video quality assessment metric is proposed for user generated content videos. The proposed approach is divided into two steps. Firstly, the encoding and content-based features are extracted at the frame level. Secondly, an ensemble-based prediction model is employed to exploit the extracted frame-level features for estimating the visual quality score for each frame. Finally, max pooling is performed to estimate the final video level quality score. We also study various score predictors to eventually suggest the best performing ensemble-learning method for the proposed model. Experiments are performed on the benchmark ICME grand challenge dataset of user generated content videos. The model is compared with several state-of-the-art user generated content video quality metrics. The observed results indicate that the proposed no-reference model outperforms the existing approaches for quality estimation of user generated content videos.
Application of Recurrent Graph Convolutional Networks to the Neural State Estimation Problem

Neural State Estimation (NSE) is a novel application of deep learning which is concerned with interpolating the state of a distribution power grid from a limited amount of sensor data and can be represented as a non-linear graph time-series nowcasting problem. Although several authors have proposed their solutions for NSE, there is neither a comparison of approaches nor an industry-standard state of the art model yet. The main purpose of this paper is to compare these solutions to a promising new approach: recurrent graph convolutional neural networks. There are theoretical reasons to assume that this class of models is suited for solving NSE. Our experiments verify that they achieve similar performance while also presenting many unique advantages compared to the previously proposed models.
SISTEM INFORMASI PENGARSIPAN PADA KANTOR KELURAHAN BALAM SEMPURNA KOTA

The Balam Sempurna Kota Kelurahan office needs an information system that can help with mail management. Management of letters in the City Perfect Balam Kelurahan Office that uses manual errors often occur in the storage of letter data and search letters. The filing information system in the Balam Sempurna Kota Kelurahan Office is very necessary, in addition to the management letter, it is also needed to make the letter faster and more efficient. This filing information system changes the way in which manual mail is stored into a computerized letter archive in the form of a computerized system. This filing information system provides good benefits for the organization. The archiving information system implementation displays a user interface, which is: the interface of all users and the administrator's interface. Filing information systems can make outgoing mail faster and more efficient, sending incoming mail data. Can be used to manage the mail archive, so that it can be managed properly.
A Basic Study for Developing an Academic Writing Program for Korean Learners for Research - Focusing on Learners’ Needs Analysis -

This study proposes the direction of an education program on academic writing skills by analyzing the needs of Korean learners in the context of research. Accordingly, we examined the needs of Korean learners majoring in Korean by collecting language samples and conducting interviews through an experiment. Based on the needs analysis, this study proposes the following. First, it is necessary to educate learners on the concepts and methods of paraphrasing, quoting, and summarizing. Second, sufficient practice opportunities and feedback should be provided. Third, professors’ understandings of the major-related knowledge or professional field should be assumed. Fourth, when collecting expressions related to academic writing skills and practicing writing, operating it as collaborative learning can be more effective. Fifth, learners often prefer intensive short-term programs. Sixth, there is a need to connect learners’ research topics and assignments.
Automatic Numeral Recognition System Using Local Statistical and Geometrical Features

Optical Character Recognition (OCR) research includes computer vision, artificial intelligence, and pattern recognition. Character recognition has garnered a lot of attention in the last decade due to its broad variety of uses and applications, including multiple-choice test data, business documents (e.g., ID cards, bank notes, passports, etc.), and automatic number plate recognition. This paper introduces an automatic recognition system for printed numerals. The automatic reading system is based on extracting local statistical and geometrical features from the text image. Those features are represented by eight vectors extracted from each digit. Two of these features are local statistical (A, A th), and six are local geometrical (P1, P2, P3, P4, P5, and P6). Thus, the database created consists of 1120 statistical and geometrical features. For the purpose of recognition, the features of the test image are compared with the features of all the images saved in the database depending on the value of the Minimum Distance (MD). All digits (0–9) were identified with 100% accuracy. The average computational time required to recognize a numeral at any font size is 0.06879 seconds.
Research on Air Gap Monitoring Technology of Hydro-Generator Based on Infrared Monocular Visual Image Analysis

The existing hydorpower generator air gap monitoring methods mainly include static monitoring and dynamic monitoring. The static monitoring method uses the wedge plug at the end to measure the rotor and lower the static air gap. However, this method is susceptible to human factors. It cannot accurately measure the contour curves of the stator inner circle and rotor inner circle relative to the rotation centre of the large axis. The dynamic monitoring method uses a sensor fixed on the stator surface to measure the air gap, but the existence of a magnetic circuit is affected. Therefore, this paper presents an approach based on the infrared uniocular visual image, extracting the stator and rotor, and rotor profile, features, and optimal threshold selection, combined with the G.A. algorithm and dynamic analysis of the air gap distance otsu algorithm. This method detects the low influence of the generator rotor air gap on the rotor magnetic path, has the advantages of real-time reliable, easy operation, dramatically reduces the operation Personnel inspection work intensity, can timely know the air gap distance, provides a new way for the state monitoring of the generator, and provides a guarantee for the safe and stable operation of the unit.
Lessons Learned from the CYK Algorithm for Parsing-based Verification of Hierarchical Plans

Verification of hierarchical plans deals with the problem of whether an action sequence is causally consistent and can be obtained by a decomposition of a goal task. This second sub-problem (finding the decomposition) makes the verification problem NP-hard. The task decomposition structure is very close to a parsing tree of context-free grammar (CFG). Recently, the CFG-parsing algorithm by Cocke–Younger–Kasami (CYK) has been modified to verify hierarchical plans efficiently. Despite being fast, the algorithm can only handle totally-ordered planning domains. In this paper, we ask whether the ideas from the CYK algorithm can be extended to a more general parsing-based approach that covers all planning domains, i.e., including partially ordered ones. More specifically, we study the effect of modifying the domain model by limiting the number of sub-tasks in decomposition methods to two and the effect of changing the parsing strategy.
CLINICO E NUTRICIONAL DE CRIANÇAS E ADOLESCENTES VIVENDO COM FIBROSE CÍSTICA ACOMPANHADOS EM UM CENTRO DE REFERÊNCIA NO ESTADO DO RIO DE JANEIRO APÓS O PRIMEIRO ANO DA PANDEMIA PELO COVID-19

CASE REPORTSa middle-aged man with acute intestinal obstruction due to an ileo-ileal intussusception of inverted Meckel's diverticulum with a lipoma that was managed by laparoscopy.Worthy of note is the very scarce number of case reports on this exceeding uncommon association.
EVOLUÇÃO CLINICA DE ADOLESCENTES COM FIBROSE CISTICA HOSPITALIZADOS POR COVID-19: RELATO DE SÉRIE DE CASOS

CASE REPORTSa middle-aged man with acute intestinal obstruction due to an ileo-ileal intussusception of inverted Meckel's diverticulum with a lipoma that was managed by laparoscopy.Worthy of note is the very scarce number of case reports on this exceeding uncommon association.
Penyuluhan Penggunaan Energi Listrik yang Efisien di Desa Banyumulek, Kediri, Lombok Barat

Banyumulek village, Kediri sub-district is the center of the pottery industry in West Lombok Regency, NTB. Pottery is produced using traditional equipment and additional equipment that uses a power source for the production process. An understanding of how to use electrical equipment to reduce production costs and efficiency in consumption of electrical energy needs to be given to the public. The community service team of the Department of Electrical Engineering, University of Mataram provided counseling about this. The counseling was held at the Banyumulek village office which was attended by the village community and the Satria Rinjani youth group. The results of the evaluation based on the questionnaire analysis obtained that the majority were of productive age, i.e. 91.67% with an education level of 58.33% were high school and above, but all of them had never received counseling on the use of efficient electrical energy. The behavior of saving electricity is good, as much as 83.33%, even though they don't know how to use electricity efficiently.
IMPLEMENTAÇÃO DE UM MODELO TELESSAÚDE PARA PESSOAS COM FIBROSE CÍSTICA DURANTE A PANDEMIA DA COVID-19

CASE REPORTSa middle-aged man with acute intestinal obstruction due to an ileo-ileal intussusception of inverted Meckel's diverticulum with a lipoma that was managed by laparoscopy.Worthy of note is the very scarce number of case reports on this exceeding uncommon association.
Supplemental Material: Hadean tectonics: Insights from machine learning

&lt;p&gt;Details on machine learning analysis of zircon composition dataset. &lt;/p&gt;
PEMANFAATAN DATA PENGINDERAAN JAUH DAN SISTEM INFORMASI GEOGRAFIS (SIG) UNTUK ANALISA BANJIR (STUDI KASUS: KECAMATAN WANAREJA KABUPATEN CILACAP)

Wanareja Subdistrict is one of 24 subdistricts in Cilacap Regency which experiences floods every year. In 2022, until September, Wanareja District will experience four floods. Utilization of remote sensing and Geographic Information Systems (GIS) can be used to determine the level of vulnerability to flood disasters. This study aims to process the parameters that cause flooding and create a flood hazard map using Geographic Information System (GIS) aplikasi. The method used is scoring, weighting, and overlaying the parameters that cause flooding, namely land use, rainfall, slope, altitude, soil type, and river buffer which are processed using the ArcGIS 10.8 application. The results of this study are in the form of a flood vulnerability map which shows that Wanareja District has three levels of flood vulnerability, namely safe, low, and moderate. The low vulnerability level is the area that has the largest area, namely 9927.26 Ha (52%), while the medium vulnerability level is 7254.53 Ha (38%), and the safe vulnerability level has the smallest area, namely 1909.09 Ha (10%) of the total area in the Wanareja District of 19090.88 Ha
EMERGING THREAT OF DEEP FAKE: HOW TO IDENTIFY AND PREVENT IT

Although manipulations of visual and aural media have been around for as long as there have been media, the relatively recent introduction of deep fakes has marked a turning point in the creation of fake information. Deep fakes are automated methods that allow the creation of fake information that is becoming increasingly difficult for human observers to see. These procedures are made possible by the most recent technological advancements in artificial intelligence and deep learning. Deep Learning is a powerful method that is now being implemented in a variety of industries, including natural language processing, computer vision, image processing, and machine vision. Deep fakes are created by the use of deep learning algorithms in order to synthesize and modify photos, videos, or sounds of a person, to the point that human people are unable to discern the fake from the real one. In this article, we present a workable description of deep fakes as well as an outline of the technology that lies underneath them. In order to assist people in thinking about the future of deep fakes, we outline the benefits of the deepfake as well as the potential threats. This study presents a complete analysis of deep fake methods and discusses the most effective strategies for preventing counterfeiting.
AN OBSERVATION CONCERNING THE REPRESENTATION OF POSITIVE INTEGERS AS A SUM OF THREE CUBES

In recent years there has been significant progress on the problem of representing integers as a sum of three cubes. Most significantly are the relatively new solutions found by Booker and Sutherland involving integers with as many as 21 digits. In this paper, we look closely at the solutions that have been found, associate to them a pair (γ,s), where γ is an algebraic number in the associated pure cubic field, and s is a positive integer, and describe an algorithm to compute this pair, which in some cases appears to be competitive with existing methods to solve the original representation problem.
Optical Illusion Images Dataset

Human vision is capable of performing many tasks not optimized for during its long evolution. Reading text and identifying artificial objects such as road signs are both tasks that mammalian brains never encountered in the wild but are very easy for us to perform. However, humans have discovered many very specific tricks or illusions that cause us to misjudge the color, size, alignment, and movement of what we are looking at. A better understanding of these phenomenon could reveal insights into how human perception achieves these extraordinary feats. In this paper we present a dataset of 6,725 illusion images gathered from two websites, and a smaller dataset of 500 hand-picked images. We will discuss the process of collecting this data, models trained on the data, and the work that needs to be done to make this information of value to computer vision researchers.
Applications to Integer and Behavioural Sequences

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The Impact of Human Capital on Digital Literacy Index

Human capital is becoming an increasingly important factor in rural economic development.Economic research, however, has not provided clear empirical support for the relationship between human capital investment and economic growth.This paper applies to stock and flow concepts to human capital and suggests an operational approach for using stock and course concepts to analyse the impact of human capital investments through education on economic growth.This paper has two main goals.First, assess and measure gaps in human capital stock in this country.It shows how effectively the different regions improve human capital stock and how long it will take to bring developing countries up to date with current levels of human capital in industrialized countries.In contribution to the occupation of human capital economic growth, the proposed employment decomposition method growth is also affected by the development of human capital gross output per worker.The proposed method introduces job growth broken down by job growth elasticity.Assume employment growth increases with human capital elasticity will decrease, making the economy less labor-intensive, leading to higher economic growth.The proposed method emphasizes micro links between human capital and the labor market.This work aims to examine the relationship between human capital and economic development.The study analyzes datasets from previous works, reviews previous literature, and draws some conclusions on human capital and economic growth.The paper summarizes articles on human capital in terms of the theoretical framework of economic growth theory, the neo-classical growth model, the Solow growth production function, the new endogenous theory, and empirical evidence on the
El uso del foro en Educación Superior: aplicación para la asignatura "Economía de la Empresa: dirección y organización"

Teaching innovation activities, based on the use of information and communication technologies, are becoming increasingly important. Such activities allow the development of learning spaces based on academic discussions that favor students´ critical thinking development based on communication. In this context, the forums are acquiring great relevance because they allow the students to be placed in a certain problem, motivate them to intervene in the discussion and give them the opportunity to contribute with their point of view. The present paper analyses the experience developed in the use of forums in the subject Business Economics: Management and Organization in the Degree in Business Administration and Management (ADE) and in the double degree in ADE and Law in the 2021-2022 academic year from the Faculty of Economics and Business of the University of A Coruna. Once the forums were developed, a survey was carried out to the students whose results show that the most valued aspects of the forums for Business Administration students and for Business Administration and Law students are the perceived usefulness -related to the dimension of technological acceptance of the tool- and the perceived self-efficacy respectively -related to the cognitive social dimension provided by the tool. Regarding the least valued aspects of the forums, both Business Administration students and Business Administration and Law students point to the perceived ease of use -related to the dimension of technological acceptance of the tool-.
Crebando miolos. A promoción da aprendizaxe cooperativa a través da técnica puzzle

This experience of teaching innovation has been designed for face-to-face teaching in the subject Information and communication technologies applied to speech therapy intervention, optional for the 3rd year of the Degree in Speech Therapy. Due to its characteristics, this proposal could be adapted to part-time teaching or even teaching in a completely virtual format. Based on the application of the puzzle technique and with various phases (moving from individual to cooperative work, through the group), the dynamic is based on gaining a broad knowledge of applications and web resources useful for speech therapy intervention, culminating in the creation of a virtual and collective environment for learning that collects all the work developed throughout the course, of present and future utility. With the emphasis on promoting student participation and motivation, from a truly cooperative approach, and from an orientation to content creation, the results allow us to contrast the effectiveness of the proposal in the dimensions mentioned, both academically and in teacher and student satisfaction. However, the designed methodology seems useful to address the competencies of this subject, with the possibility of being applied in other degrees, subjects or courses, with the relevant adaptations.