Reviewerly/exHarmony huggingface dataset:
Perbandingan Face Recognition dan QR Code Dalam Sistem Absensi Menggunakan Geolocation Berbasis Mobile

Abstract— The development of increasingly sophisticated technology makes mobile devices become main alternative in managing life's affairs. Mobile device that offers services and computing is a smartphone. The sophistication of smartphone technology can be used to process attendance. Attendance system is a system that can record presence of each user, attendance system can be processed using several types of attendance including conventional attendance using a signature and digital attendance using Face Recognition and QR code. Processing attendance system, the geolocation feature can be used to find location. This study aims to explain and determine the best digital attendance method between Face Recognition and QR code using geolocation. Based on the explanation of previous research and comparing the Face Recognition and QR code methods in processing the attendance system, the results obtained that the QR code method is the best method for digital attendance because it has high accuracy and is easier to implement.&#x0D; Key Words— Attendance System, Mobile Device, Geolocation, Face Recognition, QR code
Pairwise Alignment of Archaeological Fragments Through Morphological Characterization of Fracture Surfaces

Abstract We design a computational method to align pairs of counter-fitting fracture surfaces of digitized archaeological artefacts. The challenge is to achieve an accurate fit, even though the data is inherently lacking material through abrasion, missing geometry of the counterparts, and may have been acquired by different scanning practices. We propose to use the non-linear complementarity-preserving properties of Mathematical Morphology to guide the pairwise fitting in a manner inherently insensitive to these aspects. In our approach, the fracture surface is tightly bounded by a concise set of characteristic multi-local morphological features. Such features and their descriptors are computed by analysing the discrete distance transform and its causal scale-space information. This compact morphological representation provides the information required for accurately aligning the fracture surfaces through applying a RANSAC-based algorithm incorporating weighted Procrustes to the morphological features, followed by ICP on morphologically selected ‘flank’ regions. We propose new criteria for evaluating the resulting pairwise alignment quality, taking into consideration both penetration and gap regions. Careful quantitative evaluation on real terracotta fragments confirms the accuracy of our method under the expected archaeological noise. We show that our morphological method outperforms a recent linear pairwise alignment method and briefly discuss our limitations and the effects of variations in digitization and abrasion on our proposed alignment technique.
Enhancing a student productivity model for adaptive problem-solving assistance

Research on intelligent tutoring systems has been exploring data-driven methods to deliver effective adaptive assistance. While much work has been done to provide adaptive assistance when students seek help, they may not seek help optimally. This had led to the growing interest in proactive adaptive assistance, where the tutor provides unsolicited assistance upon predictions of struggle or unproductivity. Determining when and whether to provide personalized support is a well-known challenge called the assistance dilemma. Addressing this dilemma is particularly challenging in open-ended domains, where there can be several ways to solve problems. Researchers have explored methods to determine when to proactively help students, but few of these methods have taken prior hint usage into account. In this paper, we present a novel data-driven approach to incorporate students’ hint usage in predicting their need for help. We explore its impact in an intelligent tutor that deals with the open-ended and well-structured domain of logic proofs. We present a controlled study to investigate the impact of an adaptive hint policy based on predictions of HelpNeed that incorporate students’ hint usage. We show empirical evidence to support that such a policy can save students a significant amount of time in training and lead to improved posttest results, when compared to a control without proactive interventions. We also show that incorporating students’ hint usage significantly improves the adaptive hint policy’s efficacy in predicting students’ HelpNeed, thereby reducing training unproductivity, reducing possible help avoidance, and increasing possible help appropriateness (a higher chance of receiving help when it was likely to be needed). We conclude with suggestions on the domains that can benefit from this approach as well as the requirements for adoption.
Visual-Assisted Sound Source Depth Estimation in the Wild

Depth estimation enables a wide variety of 3D applications, such as robotics, autonomous driving, and virtual reality. Despite significant work in this area, it remains open how to enable accurate, low-cost, high-resolution, and large-range depth estimation. Inspired by the flash-to-bang phenomenon (i.e. hearing the thunder after seeing the lightning), this paper develops FBDepth, the first audio-visual depth estimation framework. It takes the difference between the time-of-flight (ToF) of the light and the sound to infer the sound source depth. FBDepth is the first to incorporate video and audio with both semantic features and spatial hints for range estimation. It first aligns correspondence between the video track and audio track to locate the target object and target sound in a coarse granularity. Based on the observation of moving objects' trajectories, FBDepth proposes to estimate the intersection of optical flow before and after the sound production to locate video events in time. FBDepth feeds the estimated timestamp of the video event and the audio clip for the final depth estimation. We use a mobile phone to collect 3000+ video clips with 20 different objects at up to $50m$. FBDepth decreases the Absolute Relative error (AbsRel) by 55\% compared to RGB-based methods.
AN EFFICIENT METHOD FOR SOLVING THE PROBLEM OF CHANNEL POWER DISTRIBUTION TAKING INTO ACCOUNT FUZZY CONSTRAINTS ON CONSUMPTION VOLUMES

Context. An efficient algorithm has been developed for solving the problem of rational distribution of the power of data transmission channels with fuzzy restrictions on consumption volumes. A standard solution method based on a fuzzy optimization problem is considered. A constructive variant of finding a solution based on the backtracking method is proposed.&#x0D; Objective. The goal of the work is to develop an algorithm for solving the problem of rational distribution of the power of data transmission channels with fuzzy restrictions on consumption volumes based on the backtracking method.&#x0D; Method. This paper The article proposes a method for solving the problem of rational distribution of the power of data transmission channels, taking into account fuzzy restrictions on consumption volumes. A feature of such tasks is the inability to meet the needs of the end user at the expense of the resources of different suppliers. The method of solution based on fuzzy problems of mathematical programming is considered. A constructive algorithm for solving the problem based on the backtracking method has been developed. Computational experiments have been carried out.&#x0D; Results. The developed method for solving the problem of rational distribution of data transmission channel capacities, taking into account fuzzy restrictions on consumption volumes, made it possible to solve the problem of constructing an optimal configuration of a three-level information and computer network with a given number of communication servers and taking into account fuzzy consumption volumes. &#x0D; Conclusions. Methods for solving the problem with fuzzy restrictions on the consumption volumes of end users are investigated. A fuzzy optimization problem is formulated, which allows taking into account the interval specified volumes for the connection values. A variant of solving fuzzy optimization problems in the case of using fuzzy numbers is proposed. A multi-criteria problem of efficient distribution of communication channel powers with fuzzy restrictions is formulated. A variant of the algorithm with a return is proposed, which allows solving the obtained problem. The approach is illustrated by a number of numerical examples for the problem of forming a network structure with a given number of end users and different allowable bandwidths of communication servers.
On the Gradience of English Size Nouns: frequency, productivity, and expansion

The synchronic degrees of grammaticalization of size nouns are traditionally measured based on proportionate frequencies of their quantificational attestations in corpus samples. However, grammaticalization, in general, is associated not only with an increased frequency of grammaticalized uses but also with a rise in productivity and distributional expansion. Thus, drawing on corpus data encompassing selected English size nouns which originally individuate concrete inanimate nominals, this paper investigates the relationship between the three aforementioned parameters. Productivity is operationalized as the arithmetic mean of two measures, namely type-token ratio (TTR) and hapax-token ratio (HTR), i.e. the number of, respectively, types of quantified collocates and hapax legomena N2s divided by the number of all quantifier tokens of each expression, while host-class expansion is construed as the proportion of animate and abstract collocates among the respective items’ quantifier uses. Contrary to expectations, the results reveal only a weak positive correlation between the elements’ frequency values and their levels of productivity, and the same holds for the relation between frequency and distributional extension. Also surprising is the moderate negative correlation observed between productivity and expansion, which can nevertheless be elucidated in terms of a high type frequency of semantically general animate and abstract N2-collocates of the most distributionally extended expressions.
Big Data' and Data Mining' Role in Fight Against Drug Trafficking

The subject of the research is the ways of using modern Big Data and Data Mining methodologies to improve the process of lawmaking and law enforcement practice in the field of illicit trafficking of new psychoactive substances. Based on the experience of European countries and international experience in general, the author proves the need to create a methodology for early detection of the spread of new psychoactive substances that pose a significant threat to public health. This technique, according to the author, can be based on the use of methods of applied statistical analysis of the Google Trends database, which, in turn, can be used to combat drug crime in terms of detecting and predicting crimes. The practical significance of the conducted research lies in the development of a methodology for early detection of the spread of new psychoactive substances, which can be used to optimize the operational legislative response and improve law enforcement practice in the field of combating illicit drug trafficking. The scientific novelty of the conducted research consists in the creation of a predictive rule in the form of a linear regression equation that allows predicting the spread of such a new psychoactive substance as mephedrone in various regions of the Russian Federation, as well as planning operational investigative measures taking into account the identified risk zones. This study may be of interest to law enforcement officials, legal scholars, students and teachers of law schools.
Ultrasonic Image Monitoring of High-Risk Pregnant Women Based on Image Deblurring Method

The method of image deblurring is one of the research hotspots in the field of image restoration, and its purpose is to restore the damaged blurred image to a clear image. Under normal circumstances, the image deblurring process is the key to accurately recovering unknown images, and it is crucial that the image recovery model can be used fully and effectively when configuring the image recovery model. The main task of this paper is to use an effective optimization model to obtain a more accurate core and restore a clear image. High-risk parturients refer to high-risk parturients in pregnancy and pregnant women with high-risk pregnancy factors, and other three-dimensional ultrasound images TUI dynamic monitoring technology provides timely clues to the fetus’s kidney length, width, and abnormal development of the fetal kidney during pregnancy and tracks the fetus Renal pelvis has different outcomes beyond the normal range. In this paper, three-dimensional ultrasound is used to examine the kidneys. At the same time, 3D ultrasound image TUI technology is used to measure the long diameter, transverse diameter, and anteroposterior diameter of the fetal kidney, and the monitoring processing system is used to measure the volume of the fetal kidney. 30 fetuses with unilateral renal pelvis anterior and posterior diameter ≥10 mm were randomly examined during the case using two-dimensional ultrasound. Using three-dimensional ultrasound TUI and VOCA technology to measure the front and back of the renal pelvis, the thickness of the kidney, the resistance index of the renal hilar renal artery, and the resistance index of the renal pelvis content, this can reduce the risk of high-risk mothers and even reduce the risk to zero.
A Review on Audio Encryption Using Chaotic Sequences and Finite Field

Audio data are used in various fields such as education, engineering, mathematics, art, advertisement, military, medicine, scientific research, and many more. This excessive growth of audio data boosts the importance of multimedia data processing tools and digital documentation. This access to multimedia data through the internet has created inappropriate prospects which are hazardous for the confidentiality and integrity of the data. To encounter these threats, the domain of audio data security gains broad attention. A considerable number of algorithms have been established to protect personal information over open networks. Finite fields are well-studied algebraic structures with enormous efficient properties which have applications in the fields of cryptology and coding theory. Here, an existing system uses lossless binary Galois field extension based efficient algorithm for audio data encryption. The architecture hired a special type of curve in the diffusion module which depends on efficient elliptic curve arithmetic operations. So, it generates pseudo-random numbers (PRN) and with slight computational efforts, it produces optimum diffusion in the encrypted multimedia files. The method is compared with the proposed system using a scheme uses Henon chaotic map and 128-bit AES secret key in order to generate the cipher audio data. Henon chaotic map is a two dimensional iterated discrete dynamic system that shows chaotic character on specific values of the constants used. Chaotic maps are very sensitive to the initial parameters, i.e., a slight change in the initial conditions drastically changes the overall output generated by the chaotic system. The investigational outcomes through different analyses and time complexity demonstrated the ability of the techniques to counter various attacks. Furthermore, two schemes are compared and more appropriate to be applied for data security.
Spatiotemporal Image Quality of Virtual Reality Head Mounted Displays

Abstract Virtual reality (VR) head mounted displays (HMDs) require both high spatial resolution and fast temporal response. However, methods to quantify the VR image quality in the spatiotemporal domain when motion exists are not yet standardized. In this study, we characterize the spatiotemporal capabilities of three VR devices: the HTC VIVE, VIVE Pro, and VIVE Pro 2 during smooth pursuit. A spatiotemporal model for VR HMDs is presented using measured spatial and temporal characteristics. Among the three evaluated headsets, the VIVE Pro 2 improves the display temporal performance using a fast 120 Hz refresh rate and pulsed emission with a small duty cycle of 5%. In combination with a high pixel resolution beyond 2k x 2k per eye, the VIVE Pro 2 achieves an improved spatiotemporal performance compared to the VIVE and VIVE Pro in the high spatial frequency range above 8 cycles per degree during smooth pursuit. The result demonstrates that reducing the display emission duty cycle to less than 20% is beneficial to mitigate motion blur in VR HMDs. Frame rate reduction (e.g., to below 60 Hz) of the input signal compared to the display refresh rate of 120 Hz yields replicated shadow images that can affect the image quality under motion. This work supports the regulatory science research efforts in development of testing methods to characterize the spatiotemporal performance of VR devices for medical use.
Vocational Education with Social Distancing: Data from Online Platforms

This is a study of how vocational education was transformed to deal with social distancing due to coronavirus infection in the Russian Federation. Data was taken from online delivery platforms such as Coursera, Timepad, and Edumarket. The demand for educational courses in Russia increased by 2.5 times in the first half of 2020 due to the spread of COVID-19. Despite this only 19% of learners are prepared to continue their learning after the quarantine measures are lifted. In the first half of 2020 programs on these platforms were focused on soft skills. There was an increase in programs for stress resistance, leadership, productivity, business, hobbies and art, parent-child relationships, and foreign language learning. The proportion of programs reliant on social communications decreased significantly. However, there was an increase courses in IT (blog / website development, machine learning), and medicine (ensuring safety in case of coronavirus infection, prevention of COVID-19, etc.). The study is of interest to the heads of regional educational departments, specialists of the continuing education in universities, professional educational organizations, non-governmental organizations of continuing education, labor exchange and those who are involved in continuing education and self-learning.
SUDDENNESS FACTOR IN CRIMINAL INVESTIGATION PROCESS

In times of terrorism and other serious cross-border crimes, both the European Union and its member states are responsible for providing security for their citizens, because these crimes endanger the rights and interests of citizens.Therefore, law enforcement institutions have to conduct an objective and comprehensive investigation of all circumstances of the crime using the possibilities provided by the criminal investigation tactics and methods.Suddenness is the key to success in criminal investigation process.However, the suddenness factor can be used by both opposing sides involved in the criminal investigation process: both by the investigator in relation to the person under investigation and his / her related persons, and also by the counteracting party ñ in relation to the investigator and other participants of the investigation process.The purpose of suddenness of the investigatorís actions is to achieve the effect of their unexpectedness.Unexpected can be time of actions, place of actions, content of actions, participants of investigative actions.This study provides the theoretical framework for understanding of which elements of suddenness are especially important in law enforcement specialistsí work practice, when they have to deal with different aspects of international criminality.This paper provides also those problemsí analysis that may occur when enforcement institutionsí specialists are involved in the international cooperation for disclosing international crimes.Accumulating knowledge about these problems will create the basis for more efficient international cooperation between law enforcement institutions of Latvia and other countries in the future.
ASSESSMENT ON THE IMPLEMENTATION OF READING INTERVENTION PROGRAM IN THE NEW NORMAL

This study wanted to review the implementation of the reading intervention program to the comprehension skills of pupils in Lucban District so that necessary improvements could be made to enhance its effectiveness.Specifically, it envisions assessing the implementation of the Reading Intervention Program in the New Normal.The study sought to answer the following questions: What is the level of Implementation of the Reading Intervention Program with regards to: Attainment of Objectives, Reading Skills Developed, Teaching Strategies Used, and Adequacy of Resources/ Materials Used?What is the extent of Reading Comprehension Skills in terms of: Making Inferences, Predicting, Noting Details, Visualizing, and Questioning?Is there a significant effect of the Reading Intervention Program to the Reading Comprehension Skills?Is there a significant effect of the Reading Intervention Program to the Reading Comprehension Skills?This study is also set to test the hypothesis formulated for the study: HO1: There is no significant effect on the Assessment of the Implementation of the Reading Intervention Program to the Comprehension Skills in the New Normal.This investigation used Likert Scale question -the questions used statements, and a respondent then indicates how much they agree or disagree with that statement.The study data were taken from a total of 76 Grades IV-VI teachers as respondents.The teacher respondents were purposively selected from different public elementary schools of Lucban District.The Hypothesis stating that there is no significant effect on the Assessment on the Implementation of Reading Intervention Program to the Comprehension Skills in the New Normal is partially accepted.In view of the findings and conclusion of the study, the following recommendations were hereby presented for consideration; The reading intervention program may be systematically implemented and maintained in Lucban District; Results of the study would be presented in an academic forum to shed light on the processes and effectiveness of the reading intervention program in the Lucban District; To the School Administrators that they may consistently review the results of the study and present it in an academic forum to shed light on the processes and effectiveness of the reading intervention program in the Lucban District; It is also recommended that teachers themselves may continue to assess the results of the reading intervention program being implemented to achieve a not just some learners that can read but most learners that can comprehend what they are reading.Future researchers may use this study as their guide for other possible variables that may significantly correlate with the reading intervention program and its effectiveness.