Reviewerly/exHarmony huggingface dataset:
Animal Image Classifier Based on Convolutional Neural Network

In modern society, there are dogs and cats around people, as well as rare wild animals living in nature. The relationship between human beings and animals is getting closer and closer. The rapid development of machine learning and deep learning technology has been widely used in the academic field. Aiming at the problem of animal image classification, this paper uses Pytorch to learn about 10,000 pictures containing cats, dogs, and wild animals (tiger, lion, etc.) based on the research algorithm of convolutional neural network in the field of image classification. And a convolutional neural network model that can realize the animal image classifier is established and optimized, so that the model can efficiently classify cats, dogs and wildlife pictures. The results show that the accuracy of the two models is above 90%, and the model loss ranges from 0.706 to 0.061, and 0.807 to 0.051, respectively, showing the characteristics of good model fitting effect and strong optimization ability. Meanwhile, The accuracy of the model can be increased by properly increasing the number of full connection layers. Therefore, by constructing the convolutional neural network, the accurate detection of national ecological protection animal images can be realized.
Estimating rooftop photovoltaics placement on administrative building using Building Information Modelling

The implementation of renewable energy sources and energy efficiency measures for administrative buildings, contribute for reduction of costs for electricity and other fuels. For estimating the optimal rooftop photovoltaic placement on administrative building, a placement analysis is needed. This analysis enables designer to define the optimal placement of the PV modules on the roof using Building Information Modelling (BIM). BIM is based on digital technologies developed with the special purpose for creating a digital model of a building that contains all its physical and functional characteristics and enables easier development of PV system integrated in building. The selected administrative building has a very irregular roof divided on 14 separated rooftops with different orientation and slope. To obtain efficient PV system, the rooftop photovoltaics placement analysis is realised in three different scenarios when all 14 different rooftops are covered by PV modules, 10 rooftops facing north or the ones between other rooftops where shading is imminent, are exempt and 5 rooftops have longer exposure to sun light, or more than 1000 hours per year. The PV system, designed on 5 selected rooftops contains 335 PV modules with a total power of 135 kW and estimated annual production of electricity of 144 074.26 kWh.
Challenges of Using Information and Communication Technology in Teaching English in Nepal

Nepal government has initiated the policy of integrating Information and Communication Technology (ICT) at school level education with the hope of empowering quality in education by enhancing teachers’ and students’ knowledge, confidence and skills in ICT use. In this scenario, this study aimed to investigate the challenges in implementing ICTs in language education from teachers’ perspectives. For this objective, sequential explanatory mixed method research design was used. Questionnaire, interview and observation were the tools used for data collection from 40 purposively selected secondary level English teachers. Quantitative data were analyzed statistically while qualitative information was analyzed textually. Both the results were integrated and interpreted in discussion. The findings exhibited that teacher and policy-related obstacles were the significant challenges than institution/school-related ones. The findings indicate that teachers are in need of immediate training on ICT use in language teaching to enhance their professionalism in ICTs and adequate ICT policy should be implemented to achieve optimum opportunities and reduce the challenges.
Semantic Mapping for Domain Analysis: Identification of Discursive Practice in the Mining Arena in Southeastern Pará

This book explores the latest advances in how knowledge organisation can both draw upon and inform diverse disciplines and technological developments. It explores how best to combine theory and practice, with its contents considering practical solutions as well as the theory behind the design, development and implementation of knowledge organising systems, ranging from controlled vocabularies, classification systems and metadata schemas to ontologies and taxonomies. With contributions by Carmen Agustín-Lacruz, Mayukh Bagchi, Mario Barité, Maria Teresa Biagetti, Briony Birdi, Lynne Bowker, Thiago Henrique Bragato Barros, Ana Inés Brozia, Gema Bueno-de-la-Fuente, Julia Bullard, Rafael Cacciolari Dalessandro, José Augusto Chaves Guimarães, Christian Cole, Stephanie Colombo, Luciana Corts Mendes, Luis Corujo, Niamh Nic Daeid, Patrícia de Almeida, Hadassa De Zen Itepan, Anthony Dunbar, Jonathan Furner, Francisco-Javier García-Marco, Fausto Giunchiglia, Claudio Gnoli, Míriam Gontijo de Moraes, Hazlem Granados-Amaya, Hugo Alberto Guadarrama-Sánchez, Carlos Guardado da Silva, David Haynes, Ania Hernández Quintana, Philip Hider, Chris Holstrom, Eva Hourihan Jansen, Fidelia Ibekwe, Mat Kelly, Michael Kleineberg, Nair Yumiko Kobashi, Deborah Lee, Maël Le Gall, Joaquín López del Ramo, Luís Miguel Oliveira Machado, Hugo Moquet, Catalina Naumis-Peña, Mirtha Rauch, Mariana Ramos Crivelente, Raissa Resende de Moraes, Jorge Revez, Riccardo Ridi, Somayeh Roshan, Clarissa Schmidt, Negin Shokrzadeh Hashtroudi, Richard P. Smiraglia, Mariângela Spotti Lopes Fujita, Adriana Suárez-Sánchez, Erik Stubkjwær, Rick Szostak, Seyed Mahdi Taheri, Marc Tanti, Ana Lúcia Terra, Amanda Terrero Trinquete, Natalia Bolfarini Tognoli, Jéssica Beatriz Tolare, Raquel Torrão Valentim, Hyung Wook Choi and Mohsen Haji Zeinolabedini.
Iterators

There is a group of functions in DAX that are referred to as iterators, and from their name, we can infer that these functions iterate tables in the evaluation of a DAX expression. Any DAX function that ends in an “X” is an iterator, such as the “X” aggregators: SUMX, AVERAGEX, MAXX, MINX, COUNTAX. There are also “X” iterating functions that aren’t aggregators such as CONCATENATEX and RANKX. Just to make life even more confusing, there are iterating functions that don’t end in “X” such as FILTER and ADDCOLUMNS.
Using Variables: Making Our Code More Readable

We’ve managed very well so far without the use of variables in our DAX code. Indeed, variables haven’t always been around in the DAX language. They came on board in 2015, five years after DAX was first developed. In this chapter, we will elaborate on why variables are so useful when writing DAX expressions, and once you’ve learned how to utilize them, we will be including them henceforth in our expression, where applicable.
Leveraging Context Transition

In the last chapter, you learned how context transition enables you to programmatically aggregate data into dimensions and virtual tables. You could then author expressions that grouped and aggregated data at this higher granularity. Once you have learned the skill of using DAX in this way, the world of DAX opens up to you considerably. You will now be able to author more complex calculations that enable you to gain deeper data insights. In this chapter, you will be applying your knowledge of context transition to solving the following data analysis questions:
Marker and modified graph cut algorithm for augmented reality gaming

Augmented reality aims at superimposing a computer generated image on a user's view of the real world thereby creating a composite view. Virtual reality on the other hand keeps the user isolated from the real world and immersed in a world that is completely fabricated. The main objective of this research is to capture a real life image and augment it as a component of a gaming environment using the principles of augmented reality. For this research implementation, we have chosen car racing as our gaming environment. The core elements are the image segmentation using CIELAB colour space based graph cut algorithm, 2D to 3D modelling and game development with augmented reality. The tools utilised are MATLAB, insight3D and Unity3D. The proposed idea will enable someone to view a virtual environment with real components that are integrated dynamically.
Formation of Moral Qualities of Future Customs Specialists as Axiological Component of Professional Training Process

The article examines the components of the moral sphere, methods of forming the moral qualities of a customs specialist necessary for solving professional tasks, ethical norms of professional behavior of a customs officer, the principle of axiology, which implies the active inclusion of a value component in the content of an educational program, the implementation of which is aimed at the formation of universal and socially significant values of a customs specialist, an axiological approach that increases the social role education, since the value-oriented nature is characteristic of all types of human activity. The article presents the structure of the moral sphere of a customs specialist, which includes the following components: motivational-value (moral norms, values, ideals, rules and ethical principles of official behavior), cognitive (moral knowledge, value judgments, beliefs, orientations in the field of professional activity), activity (professional behavior, actions, deeds), reflexive (moral emotions, feelings, experiences, self-esteem), the content of which determines the value-semantic attitude to the surrounding space, professional activity, yourself and your actions - a professional and moral position.
Research on Speech Coding Technology Based on Nonlinear System Theory in in AI-Based Disease Detection

In order to minimize the redundancy of speech decoding and realize the reliable transmission of speech data files, a speech coding method based on nonlinear system theory is proposed. Through pitch extraction, the residual harmonic spectrum condition of speech data information is calculated, and then combined with error correction coding technology, the speech feature analysis based on nonlinear system theory is realized. On this basis, the full search vector quantizer is set to suppress the noise parameters. According to the synthesis standard of speech coding information, the smooth application of speech coding technology based on nonlinear system theory is realized. The experimental results shows that, compared with MELP coding principle, the above coding technology can fully reduce the decoding redundancy level of voice information, realize the synchronous transmission of serial and parallel voice information, and better guarantee the reliable transmission environment of voice data files.
Efek Mediasi Efikasi Diri Komputer pada Pengaruh Daya Dukung Sekolah terhadap Kompetensi Teknologi, Pedagogi, dan Konten Guru Ekonomi

The purpose of this study is to determine and to analyze the effect of school support on computer selfefficacy, the effect of computer self-efficacy on technological pedagogical and content knowledge and the effect of school support on technological pedagogical and content knowledge mediated by computer self-efficacy. The research method used was an explanatory survey and the data was collected through a questionnaire. Economics teachers at the Karawang Regency Senior High School in 2021 totaling 68 teachers were determined as the population and the saturated sample was used as \a sampling technique by taking the entire population. Data were analyzed using descriptive statistics and mediation regression analysis. The results showed that the school support had an effect on computer self-efficacy with low contributions, computer self-efficacy had an effect on technological pedagogical and content knowledge of teachers with low contributions and school support had an effect on technological pedagogical and content knowledge of teachers with low contributions through computer self-efficacy. The results of the study have implications that in the future research on technological pedagogical and content knowledge will focus on the study of developing learning systems based on the use of ICT.
Analysis of Intelligent Optimization and Allocation of Human Resources in Media Operation Management

Scientific and rational optimization of human resources allocation in media operation and management to maximize the economic and social benefits of enterprises is the top priority of the current media to strengthen human resources work. How to allocate human resources, adjust the structure of human resources, realize complementary advantages, and dynamically adapt to the needs of economic construction is a very important issue that must be carefully studied in the process of human resources development and management. In this article, a binary classification support vector machine method is proposed, which uses linear function calculation, and finally uses multi-skill model to solve performance experiments. The results show that the media operation management must reform the labor employment system, allocate the labor force scientifically and rationally, and make effective use of the media management labor resources; labor employment is a necessary means for the development and survival of enterprises. It is an important function of enterprise management to manage and utilize labor reasonably and effectively. Through optimal allocation and rational utilization, the human resource allocation in media operation management can reach a higher management level.
A Bibliometric and Visual Analysis of Interactive Distance Perception

The issue of distance and spatial cognitive differences on the process of interacting behavior is of increasing interest and involves multiple fields of inquiry. However, there is a lack of bibliometrics and literature reviews on this topic to systematically evaluate the current state of research. This study synthesizes previous research on the interactive distance perception and its related influencing factors, and summarizes it by clustering and trending the relevant research literature through bibliometrics. The conclusions show that the overall number of literatures within the search area is on the rise, and the research directions are gradually refined, with the research hotspots mainly focusing on social distance, risk perception, mental health, and influence factors and life. Relying on the theoretical system based on distance perception and interaction behavior model, the application of virtual or augmented reality interaction distance perception and virtual social life scenarios becomes a new trend for future research development.
IMPLEMENTATION OF AN ALGORITHM FOR MONITORING STORAGE CONDITIONS OF MEDICINES AND SEARCHING FOR APPROPRIATE PLACEMENTS IN A SOFTWARE SYSTEM FOR STORAGE AND CONDITION CONTROL OF MEDICINES

Analyzed the problem and programmatically implemented the algorithm to monitor storage conditions of the medicines and searching for the appropriate placements.
An Intelligent Path Planning Algorithm and Control Strategy Design for MultiMobile Robots based on a Modified Elman Recurrent Neural Network

The goal of the navigation process is to find the optimal path for the mobile robot and control its motion on that path without any oscillation.This work aims to find the optimal paths for multi-mobile robots working in the same static environment.To achieve this goal, the proposed quarter orbits particle swarm optimization (QOPSO) algorithm, which is an enhancement of the cell decomposition algorithm, will be used.The main advantage of using the QOPSO algorithm is to generate the shortest path and avoid collision with static obstacles.Moreover, to direct the motion of the three mobile robots on the desired predefined paths, a proposed inverse differential kinematic neural network trajectory tracking (IDKNNTT) controller based on a modified Elman recurrent neural network (MERNN) will be used.This proposed controller is used to control the nonlinear kinematics mobile robots' system to smoothly and quickly generate the left and right wheels' velocities of the multi mobile robots, which are used to control the orientation and position of each mobile robot.Furthermore, using the proposed controller minimizes the tracking error in the X-axis and the Y-axis positions, approximately zeroes the orientation error, and provides no oscillation in the responses.In particular, the controller guarantees that all the mobile robots will follow their desired paths quickly and correctly.Finally, we validate the numerical simulation results of the proposed control strategy by comparing them to those of other types of controllers in terms of the maximum error enhancement in the X-position and the Y-position.Particularly, when the proposed controller was compared to the convolutional neural network trajectory tracking (CNNTT) controller, the comparison results show that the proposed controller improves the tracking error rate on the X-axis by 75.5 % and enhances the tracking error rate on the Y-axis by 21.2 %.In addition, the proposed controller was compared to the MIMO-PID-MENN controller, and the comparison results show that the proposed controller improves the tracking error rate on the X-axis by 33.3 % and on the Y-axis by 40.6 %.
P IDENTIFIKASI KESIAPAN DAN KESULITAN GURU MATEMATIKA DALAM PELAKSANAAN KURIKULUM 2013 DI MASA PANDEMI COVID 19

The research method used is descriptive qualitative. Collection of primary data and secondary data. Analysis with data reduction, presentation, conclusion and verification. Research at SMA Yadika 11, SMK 4 and SMA 7 Bekasi. The results of the analysis, 1) 95% of the online learning process is still from curriculum 13, the school facilitates teachers. However, when the implementation was not in line with expectations, this was because the material provided was not prepared with the standard of the initial ability of students, the books provided were not strong enough to build concepts, educators had difficulty writing symbols, student responses to professional competence were 79%, 70% of participants students assess that teachers do not have teaching materials and modules used as learning aids, observing 4 teacher materials have difficulty explaining related to writing symbols and proof. 2) The form of readiness by providing textbooks as the main source, however, books with cognitive dimensions. Lots and not hot books, this is not in line with curriculum 13. 3) The assessment method is prepared by the teacher, however, the assessment method is not given and the material tested is more difficult than what is taught and 60% disagrees with the teacher's assessment method.
An Improved Crucible Spatial Bubble Detection Based on YOLOv5 Fusion Target Tracking

A three-dimensional spatial bubble counting method is proposed to solve the problem of the existing crucible bubble detection only being able to perform two-dimensional statistics. First, spatial video images of the transparent layer of the crucible are acquired by a digital microscope, and a quartz crucible bubble dataset is constructed independently. Secondly, to address the problems of poor real-time and the insufficient small-target detection capability of existing methods for quartz crucible bubble detection, rich detailed feature information is retained by reducing the depth of down-sampling in the YOLOv5 network structure. In the neck, the dilated convolution algorithm is used to increase the feature map perceptual field to achieve the extraction of global semantic features; in front of the detection layer, an effective channel attention network (ECA-Net) mechanism is added to improve the capability of expressing significant channel characteristics. Furthermore, a tracking algorithm based on Kalman filtering and Hungarian matching is presented for bubble counting in crucible space. The experimental results demonstrate that the detector algorithm presented in this paper can effectively reduce the missed detection rate of tiny bubbles and increase the average detection precision from 96.27% to 98.76% while reducing weight by half and reaching a speed of 82 FPS. The excellent detector performance improves the tracker's accuracy significantly, allowing for real-time and high-precision counting of bubbles in quartz crucibles. It is an effective method for detecting crucible spatial bubbles.
Linked Open Data and Medieval Studies: Some Lessons from the Mapping Manuscript Migrations Project

Building on the work of the Mapping Manuscript Migrations (MMM) Project between 2017 and 2020, this article aims to identify the potential benefits and likely challenges of using Linked Open Data (LOD) more widely across the research field of medieval studies. As well as aggregating and linking disparate datasets relating to the history of more than 220,000 medieval manuscripts, the MMM Project reconciled and matched vocabularies for places, persons, organizations, works and manuscripts. It built and tested various forms of access to the aggregated data, including a web portal and a SPARQL endpoint. It also demonstrated suitable ways of publishing its outputs, not only the aggregated data but also the data model and ontologies used. Drawing on the lessons learned in the MMM Project, the article offers suggestions for building an LOD environment for Western European medieval studies more broadly, covering the aggregation of heterogeneous data, the reconciliation of disparate vocabularies, and ways of enabling more effective discovery, exploration and analysis across the aggregated data.
Methodology for structuring a dataset of cervical cell images for the study of malignancy changes associated in conventional Pap Test

The Pap test is a screening procedure used worldwide for the diagnosis of cervical cancer. The MalignancyAssociated Changes (MAC) are slight morphological and textural changes that take place in the chromatin ofthe cell nucleus. Their study allows the early detection of several types of cancers. However, the number ofdata set for MAC studies is limited by the technical aspects that must be followed. In this work, we createda data set for the study of MAC in images of cervical cells from conventional cytology exams. To extract thecharacteristics of the nuclei, the color channels were separated by the contribution of Hematoxylin and Orange G6dye, which identified morphological, illumination and texture characteristics. As a result, 1186 nuclei of patientseither with some type of anomaly or without anomalies were obtained. To separate the regions of the nuclei, thenon-linear regression function and theWatershedalgorithm with an accuracy of 85.6 % were used. This dataset contains adequate data to complement future work in MAC study of cervical cells from conventional pap smears.