Reviewerly/exHarmony huggingface dataset:
Forensic synthetic speech inspection technique based on formant comparison

With the development of speech synthesis technology, the simulation of specific individual’s speech has gradually matured， synthetic speech is easily and perceptually recognized as real speech, which may occur frequently in illegal activities. To identify crimes, forensic technology is widely used such as comparing the formants, pitches, and rhythm. The present study aims to investigate whether the method of comparison of formants can recognize the differences between the perceptually similar synthetic speech (hereinafter “personal anchor” speech) and real speech. To this end, two young males and two young females from different dialect regions were recruited to read the same text. Their voices were recorded and used to generate four “personal anchors” by the software of sound spectrum and statistics analysis. The method of comparison of various parameters of the formant, including numerical statistical, stability analysis, and transitional segments feature were applied to analyze the differences between the real speech and the corresponding “personal anchors”. It was found that the numerical or stability analysis of formants was not sufficient to fully determine whether the speech was synthesized, while comparing the transitional segments of some specific syllables could efficiently detect the synthetic speech from the real speech.
Promosi Perpustakaan dalam Minat Kunjung di Sekolah Dasar Negri 10 Minas

The presence of libraries in the school environment is basically a process of exchanging information between authors and library users. Various definitions of libraries are discussed in various sources, but the library is defined simply by some people as a place to store collections, especially in the form of prints. This type of research uses descriptive research methods. Descriptive research is a method for examining the current state of a group of people, objects, conditions, systems of thought, or classes of events. The purpose of such descriptive research is to provide a systematic, correct and accurate description, description or description of the nature of the relationship between the phenomena studied. The method used in this study is a qualitative research method. Qualitative method is a research method that aims to obtain a comprehensive understanding of the phenomena experienced by research subjects by describing in words and language, in the context of specific experiences and using various natural methods. One of the marketing activities for library services to students is by This promotion, of course, is a means used by librarians to introduce the library to broad students so that they know and are interested in coming and using the library because a library without visitors is of no use.
Integrating the Big Data in Sports and Resource Interaction Using Artificial Neural Network

Big data is the result of balancing computing power with the need for large, rapidly updated, and comprehensive datasets and is now widely used in urban planning, medicine, and other fields. With the advent of the era of big data, the sports industry must also adapt to this change. The era of big data brings new ideas to the development of sports resource interaction. At the same time, the demand for a high-efficiency and high-performance sports big data integration system is imminent. The interaction between college sports and community sports realizes the improvement of the practical ability of the two institutions and departments through the satisfaction of people’s own needs. And it affects people’s lifelong sports and health by improving external conditions to internal factors. It improves the quality of life and maintains social stability and peace, thereby ensuring the better development of the university and the community. At present, the speed of data integration in the sports big data integration system is relatively slow. In order to solve this problem, this study introduces BP neural network in the artificial neural network. It introduces the concept of the neural network and its related formulas in detail. By using the BP neural network classification algorithm for data classification integration, this study conducts training and performance testing of the network. It links the extraction, transformation, and loading of data. The experimental results show that when the number of databases is 2, 4, 6, and 8, the time taken to load data by the system in this study is 113 s, 87 s, 64 s, and 42 s, respectively. It can be seen that the system in this study has obvious advantages in data loading compared with the data integration system of the existing system data warehouse. The system data query designed in this study is more efficient and consumes less time.
Tom Tom: A digital educational game prototype for theory of mind assessment and intervention for children with autism spectrum disorder

Autism is a neurodevelopmental disorder that compromises interaction and social communication, as well as causes behaviors that deviate from the patterns. Therefore, it causes deficits in social skills and cognitive processes inherent to the Theory of Mind, such as understanding and predicting one's own actions and the actions of others. This problem affects the school performance and social relationships of the autistic child. Thus, this article is the result of a research whose main objective was to develop the prototype of an educational digital game, called Tom Tom, for evaluation and intervention in the domain of Theory of Mind in children from 6 (six) to 8 (eight) years old. with Autism Spectrum Disorder. The elaboration and development of the game prototype consisted of pre-production (planning, elaboration of the Game Design Document), production (development of the code in accordance with what was planned) and post-production (technical, content and pedagogical validation). At the time of validation, the game was considered adequate for its purpose, being recommended as a tool that contributes to the expansion of new learning, skills and competences.
Multi-Channel Free-Space Optics Receiver Enabled by a Programmable Photonic Processor

A silicon photonic programmable processor of reconfigurable Mach-Zehnder interferometers is used to receive pairs of orthogonal spatially-overlapped beams modulated, sharing the same wavelength and polarization.The processor can automatically separate the two beams without any excess loss and no prior information on the incoming beams.KeywordsProgrammable photonic circuits, free-space
Violence Recognition on Videos Using Two-stream 3D CNN with Custom Spatiotemporal Crop

Abstract Violence may happen anywhere. One of the ways to know and oversee the violence in some places is by installing Closed-circuit Television (CCTV). The recorded video captured by CCTV can be used as proof in a law court. Violence video classification is also one of the topics being discussed in deep learning. The latest violence video dataset is RWF-2000. That dataset contains violent and non-violent videos, 5 seconds duration, 30 frames per second, with the amount of 2000 videos. That publication also has the best accuracy of 87.25% by their proposed method. In this study, we will use a Residual Network known to have the advantage of solving the vanishing gradient problem. Beside that, we also implement transfer learning from Kinetics and Kinetics + Moments in Time pre-trained data. We also test the number of frames and the location of the sampling frame range. RGB and optical flow inputs are separately trained with different configurations. The RGB input best accuracy is 89.25% with pre-trained Kinetics + Moments in Time, using frame location 49-149. The optical flow input best accuracy is 88.5% with pre-trained Kinetics, using 74 frames. We also try to sum the output of both inputs making accuracy of 90.5%.
El impacto de la COVID-19 en los estudiantes: aspectos físicos, sociales y de salud mental y su relación con el aprovechamiento académico

The pandemic caused by COVID-19 has brought great changes in the field of education, which has caused us interest in knowing if e-learning has generated impacts on the rate of failure, dropout and academic achievement; affecting also the social development, mental and physical health of students. To this end, we conducted a survey for college students that were affected by the COVID-19 pandemics, where the degree of impact of the aforementioned aspects was questioned. In the area of academic achievement, a survey was carried out on teachers, in addition to consulting the databases of the Autonomous University of the State of Hidalgo, contrasting grades, dropout rate and failure rate.
Malaria Case Presentation: The Results of a Web Based Malaria Surveillance in Plateau State, Nigeria

Nigeria bears the heaviest malaria burden of any single nation in the world and has relentlessly pursued the elimination of the disease. One of the key strategies for the elimination of malaria is increasing the specificity and sensitivity of surveillance. To this end, this study sought to determine malaria transmission along an altitudinal gradient of Plateau state, central Nigeria, while examining socio- demographic factors affecting the prevalence of malaria at these sites. Three communities each at high and low elevation areas of Plateau State in central Nigeria were surveyed for incidence of malaria cases. Information on age, gender, use of long-lasting insecticide treated nets, pregnancy status in women, and, malaria severity were recorded in 1700 study subjects. Using venipuncture method, 4ml blood samples were collected in EDTA vials for laboratory analyses. Microscopy (thick and thin blood smear techniques) and Rapid Diagnostic test were used to detect malaria parasites and determine the Plasmodium species involved. Using a propriety application (ELDACAP), real time geolocation data, socioeconomic, health, and preventative status information were also collected from all 1700 respondents. Our findings showed more cases of malaria prevalence in lowland areas compared to highland areas. The main predictors of malaria incidence were age, sex, use of ITN and the presentation of symptoms. Non-net users had more prevalence of malaria compared to users, males had a higher positive frequency compared to females, and malaria was more prevalent in the younger age group compared to older group. Malaria eradication in north-central Nigeria must take into account geographic differences, cultural and social practices, previous anti-malaria preventative measures (use of ITN), as well as the presence of asymptomatic malaria carriers who serve as reservoir in the population
Introduction to the Special Issue on Blockchain Security

Cite This Article Tian, Z., Guo, Y., Su, S., Lu, H. (2023). Introduction to the Special Issue on Blockchain Security. CMES-Computer Modeling in Engineering & Sciences, 134(1), 5–7.
Early Warning System Using Change Point Analysis to Detect Microclimate Anomalies

The agricultural sector is required to provide food products for human needs.To increase agricultural yields, precision agriculture approaches are required by the utilization of information and technology to maximize agricultural productivity.Precision agriculture systems cannot be separated from monitoring and controlling the environment.This system is necessary to keep the surrounding environment or microclimate by plants requirements.However, during the monitoring and control process, some failures may occur due to technical and non-technical problems, and they will cause damage if not treated immediately.Therefore, to keep the microclimate under control according to plant growing requirements, an early warning system is necessary.The objective of this study was to develops an early warning system for microclimate anomalies using Change Point Analysis based on evapotranspiration calculations.This system works to detect changes in microclimate anomalies caused by malfunctions in the monitoring or control system.Microclimate time-series data obtained from monitoring in the growth chamber are used to calculate evapotranspiration.To represent the environmental condition inside the systems, reference evapotranspiration time-series data estimated from climate data using Penmann-Monteith 56 model, were analyzed using Singular Spectrum Transformation (SST) to obtain the change point score.As the result of the performance test and observation, microclimate anomalies inside the growth chamber could be detected by the change point detection representing by the change point score.
Evaluation of Space Maintainer Internet Information On Turkish Websites Using Jama Benchmarks

Introduction: The aim of the search was to assess the quality and reliability of web-based information about space maintainer in pediatric patients.Methods: Research was carried out on the internet using Google search engine with the nine keywords about space maintainer.The study was conducted in Turkish on a total of 270 websites.Websites were evaluated with the quality criteria for Journal of American Medical Association (JAMA) benchmarks, Results: No websites met all JAMA criteria.3 websites met the author's criteria.9 websites were currency.There was only one website included references.None of website included disclosure criteria.Discussion and Conclusion: A large amount of information about space maintainer in pediatric patients on websites was generally inadequate.It is necessarry that internet information should be updated on a regular basis.
Socialization of Drawing Technique with Inventor Software for High School Student

In today's digitalization era, the sensitivity of using design and illustration software is a demand in improving the competencies possessed by students at the high school level. This ability will support students' interests and talents by adjusting the Project Based Learning Program owned by SMAM 1 Gresik, namely the L800 Motorcycle Modification Automotive Project. By introducing and training students using the design and illustration software used, namely Autodesk Inventor: Student Version, This training activity aims to (1) Students are able to use the Autodesk Inventor Application in 2D and 3D schemes, (2) Students are able to gain an understanding of motor engineering components and motor engineering drawings, (3) help teach teachers who teach subjects in the field of applied science. The methods used in this community service are teaching, demonstration and practice methods. The result of this community service is to improve the ability of the participants in terms of designing and modifying the practice of observing L800 motorcycle components and students more easily understand the shape of an Engineering component through Technical Drawings effectively and efficiently due to virtual 3D modeling in the Autodesk Inventor application.
INTERACTIVE LECTURES AS A WAY TO INCREASE THE EFFECTIVENESS OF TEACHING AND LEARNING IN HIGHER EDUCATIONAL ESTABLISHMENTS

The article is devoted to an interactive lecture as one of the effective methods of teaching in High educational establishments, which helps to increase the effectiveness of learning and the level of motivation of students. The authors reveal the essence of interactive learning and emphasize that it consists in the organization of constant interaction of all participants of the educational process. Also they compare the traditional classical lecture with the interactive one and highlight the features of the latter, emphasizing its benefits. The fact of the need to revise traditional forms and methods of teaching becomes obvious, as the main task of a modern lecturer is to involve HE students to active conscious learning and to digitalize the educational process. That is why the article focuses on digital tools that can help teachers to organize interaction of the participants of the educational process, create educational video content and provide constant feedback to students during and after the interactive lecture. The authors also present a number of forms of interactive lectures and tips that turn a traditional lecture into an interactive one (using active individual or group work, using of interactive activities, using of various forms of feedback to control students understanding of the material). It has been proved that digital tools have created important didactic conditions for effective organization and effectiveness of interactive lectures, due to increasing the visualization of educational material through infographics, multimedia, comics, animation and video, facilitated the organization of productive group learning activities, simplified feedback and the use of digital tools increased the motivation, independence and awareness of students about learning outcomes, increased efficiency of control and self-control by automating current and final assessment, intensified reflection on educational activities based on online surveys, commenting on forums and chats. Key words: interactivity in teaching, interactive lecture, digital tools, group work, active learning.
Deep Maxout Network for human action and abnormality detection using Chronological Poor and Rich Optimization

Human activity recognition targets to discriminate the various human actions depending on the size, shape and posture exhibited by the humans while performing a particular action. Video-based human action detection easily understands the actions and behaviours of humans in the video sequences. Therefore, it has a part in various applications, like human-machine interaction and healthcare domains. However, human activity recognition in a complex environment leads to poor performance and low accuracy, and it remains a challenging task in human action recognition using video sequences. To overcome such limitations, a Chronological Poor and Rich Optimisation (CPRO)-based Deep Maxout Network is developed for effective human movement and abnormality recognition. The CPRO is devised by integrating the chronological concept into Poor and Rich Optimisation. In the feature extraction process, the features include Histogram of Oriented Gradients, Local Gradient Pattern and hierarchical skeleton are digging out. Moreover, human action and abnormality detection are done utilising Deep Maxout Network trained by the proposed CPRO. The proposed scheme reveals superior results with respect to evaluation measures, such as accuracy, sensitivity and specificity of 0.954, 0.958 and 0.960, respectively.
Artificial Intelligence Enabled Reagent-free Imaging Hematology Analyzer

Leukocyte differential test is a widely performed clinical procedure for screening infectious diseases. Existing hematology analyzers require labor-intensive work and a panel of expensive reagents. Here we report an artificial-intelligence enabled reagent-free imaging hematology analyzer (AIRFIHA) modality that can accurately classify subpopulations of leukocytes with minimal sample preparation. AIRFIHA is realized through training a two-step residual neural network using label-free images of separated leukocytes acquired from a custom-built quantitative phase microscope. We validated the performance of AIRFIHA in randomly selected test set and cross-validated it across all blood donors. AIRFIHA outperforms current methods in classification accuracy, especially in B and T lymphocytes, while preserving the natural state of cells. It also shows a promising potential in differentiating CD4 and CD8 cells. Owing to its easy operation, low cost, and strong discerning capability of complex leukocyte subpopulations, we envision AIRFIHA is clinically translatable and can also be deployed in resource-limited settings, e.g., during pandemic situations for the rapid screening of infectious diseases.
Dual-Layer Waveform Domain Deep Learning Approach for RF Fingerprinting

The widespread deployment of wireless sensors and devices is enabling the rapid development of the Internet of Things. To address the privacy and the security issues of wireless transmissions, Radio Frequency (RF) fingerprinting techniques can be used to provide an additional layer of protection. With the emergence of deep learning solutions for identifying devices, we propose a pre-processing approach that generates dual-layer waveform domain images from the captured raw I/Q-samples which can be combined with either Multilayer Perceptron Neural Network (MLPNN) or Convolutional Neural Network (CNN) architectures for RF fingerprinting. The performance of the proposed approach is evaluated using over-the-air captured data, and when combined with CNN the approach was able to identify 12 Zigbee devices with an accuracy of 99% at 24 dB Signal-to-Noise Ratio (SNR), and 89% when the SNR is varied between 16 to 24 dB. The experimental results show that the proposed pre-processing approach results in reduced training time with minimal impact on the complexity of a CNN model.
Feature Point-Based Dense Image Matching Algorithm for 3-D Capture in Terrestrial Applications

Background and Objective: Image matching is a bottleneck that must be surpassed in photogrammetric measurement, camera calibration and computer vision.This study investigated the performances of the well-known feature point detectors in automatic matching.Materials and Methods: A large base-to-height ratio of stereo images creates perspective distortion and the selection of an objectʼs small shape properties from the image becomes difficult.Therefore, a large base-to-height ratio affects matching and measurement accuracy in photogrammetry.The relative variations on the scale of stereo images also make it difficult to create conjugate points between them.Different base-to-height and various scale stereo images were evaluated to compare the matching performance of these operators.Results: The results show that the number of matched feature points decreases when the base-to-height ratio of the images is increased.The SIFT, ASIFT and SURF operators did not match the images with a base-to-height ratio larger than 1.5 and a scale change of more than three times.Finally, ASIFT generated more matched points than SIFT and SURF.Conclusion: These findings are useful for automatic three-dimensional measurement from stereo images.Three-dimensional measurement can be performed with fewer images without any force on computer capacity.The imaging positions and point of view angles for multiview evaluations should also be planned according to the limitations of these operators.
OFFLINE OCR ALGORITHM TO DETECT KURDISH/ ARABIC CHARACTERS IN SCANNED DOCUMENT

In this paper, Algorithm named (MRWL) Max Rightmost White Line is proposed to detect Kurdish/ Arabic characters’ segmentation in scanned document (printed document), it works in preprocess and segmentation stages of OCR processes, these two stages are significant parts of OCR and affects the accuracy of algorithm. The MRWL starts to remove text margins around document to reduce processing time, then, scans to find Top Line (TL) and Bottom Line (BL) for each sentence in paragraph which can be used to measure height of characters. Based on TL and BL, the Base Line (BSL) can be detected using horizontally Most Frequency Black Pixel (MFBP) which is useful to find characters’ segmentation (Atallah and Omar, 2008)&#x0D; . Finding TL, BL and BSL of each sentence help to find characters location in document. Six phases involve in algorithm, each phase has its own functionally. The Algorithm is tested with different input documents and the average accurate rate of detected segmentations is recorded as 96.93%.