Reviewerly/exHarmony huggingface dataset:
Pedagoške implikacije digitalizacije visokoškolskog obrazovanja

Given the fact that education represent a (sub) system of society, the digitalization of society consequently results in the digitalization of education as well. Starting from the premise that the pedagogical implications of digitalization are numerous and that there are significant differences at different levels of education, the aim of the paper is to consider the pedagogical implications of digitalization when it comes to higher education. The objective is concretized within the following tasks: (a) the importance of researching the relationship between education and society; (b) presenting the differences between digital and analogue generation with implications for education, (c) pointing out to the opportunities and challenges of digitalisation within higher education. In conclusion, it is pointed out that the digitalization of education is a controversial topic with numerous implications that are significantly conditioned by the level of education to which they relate. Also, polarization in attitudes about digitalization as an exclusively positive or negative phenomenon in the educational process represents two extremes in approaches, and the potential solution lies in finding a balance.
A New Algorithm to Generate Image Sets for Classification and Forecasting Problems

Image recognition is a well-known and currently addressed problem in Artificial Intelligence. It has many practical applications, including medical image analysis, face recognition, food image analysis and image retrieval, among others. One of the main problems that arises to obtain a model for classification and forecasting is the need to have a sufficiently large set of images to be able to train the model used and subsequently validate it. The search and sorting of the images required to obtain this set is time consuming. In this work, an algorithm is presented that, from a set of images, performs different transformations in terms of shape, color, transparency, perspective, and focus, so that the set of available images is significantly increased and allows training and model validation to be carried out. Considering the proposed transformations, the construction time of the image sets is significantly reduced, and the training model is provided with relevant information for its optimization.
Fourth Industrial Revolution and Management 3.0: Conditions for the Transformation of Higher Education

The article deals with the basic contradictions between the technological level reached by the economy of various countries, including Russia, and the new paradigm of accompanied by the transition period from post-industrial to information society.Multifactorial vision of the trajectory of development as a transition to a new technological level is proposed.The necessity and peculiarities of using the concept of leadership management to ensure effective of organizations are revealed.The directions of implementation of digital technologies in the field of education to ensure rapid renewal of the country's human resources are shown.
Audio encryption by using hybrid method

This study offers a hybrid approach for encrypting sounds. The approach consists of two stages: the conversion of sound to image and encoding the sound converted to image with the hybrid method included diffractive encoding.
Best USB Microphone For Gaming

A great microphone will allow you to live in the moment, and send clear sound and instructions to your computer gaming partners. This is important for ...
Quantum Inspired Genetic Algorithm Model based Automatic Modulation Classification

The popularity of automatic modulation categorization (AMC) is high in recent years owing to the many advantages. When it comes to communication, reliability in an AMC is very critical. Increasing the amount of signals exponentially increases the cost of using the AMC. Precise classification methods, such as neural network, in which either the parameters of the neural network or the dimensions of the input or output variables are modified dynamically, are not successful in obtaining high accuracy results. To improve the accuracy of the modulation categorization, this study employs a "QIGA" feature selection model based on Quantum (inspired) Genetic Algorithm (QIGA). QIGA is used to choose the correct functionality, and to limit the number of examples that must be learned so that the overall system time is shortened and the cost of computing is reduced. Selecting excellent characteristics is enhanced via quantum computing, and this is done to lower the complexity of the solutions. The internal validation results demonstrated that the QIGA model significantly improved the statistical match quality and significantly outperformed the other models.
Prerequisites for Defining Linguistic Reflection

Human activity can be manifested in linguistic reflection that makes it possible to recognize the individual linguistic arguments and the structure of the language. It is also an instrument for the formation of individual’s linguistic etiquette depending on the person’s consideration of the language norms. The authors aimed to determine the features of the language reflection process. In the course of the work, special literature was studied, and different points of view on the definition of reflection were analyzed. The authors agree with the view that there are three types of reflection, such as simple, scientific, and philosophical. As a result of the study, the following prerequisites to determine language reflection were identified: language and thinking, language consciousness, language culture, the culture of thought, the development of language and consciousness, respect for the native language, ability to express themselves properly in any environment, respect for the milieu, and accountability for mental and emotional activities.
Convolutional Neural Networks Architecture: A Tutorial

this is a preprint version of a paper that was subsequently used as a basis for: M. Bolgkoranou and J. M. Ortiz, “Multivariate Geostatistical Simulation using Principal Component Analysis.”. It does not contain changes and edits that were made during peer review, or updates, edits and alterations by the authors and the publisher that occurred prior to acceptance and final publication
Dimensional Reduction with PCA for Feature Selection in Pedestrian Detection

The feature orientation gradient histogram (HOG) together with the classification support vector engine (SVM) is still considered the standard for detecting modern pedestrians using various features and classification schemes. In this study, we investigated and developed a HOG solution combined with SVM to achieve a robust detection method. With minor changes in shape, image direction, and location, as well as significant color changes, the proposed HOG descriptor performs well. While the HOG performed similarly in the other classes, we concentrated on upright people, or pedestrians, in this study. However, when using different cell sizes, overlaps, and block sizes, the HOG method will vary, resulting in the occurrence of high-dimensional feature vectors. Principal Component Analysis (PCA) is used to solve this problem by reducing the HOG dimensions from 3780 to 937. As a result, SVM can handle shorter feature vectors, requiring less computational time and effort. Following that, we experimented with various SVM models to find the best SVM parameters and kernel for the INRIA data set. Like the application of PCA on the Linear HOG-SVM detector, it produces a precision value of 0.952, a recall of 0.982, and an F-score of 0.967. Therefore, this study not only proposes a linear SVM detector combined with HOG as a reference for detecting pedestrians but also contributes to the research of similar tasks involving other features and objects.
Corrections to “Value sets of sparse polynomials”

Abstract We give a corrected version of our previous lower bound on the value set of binomials (Canad. Math. Bull., v.63, 2020, 187–196). The other results are not affected.
DOES IMMERSIVE VIRTUAL REALITY INDUCE CYBERSICKNESS AND IMPACT EQUILIBRIUM COORDINATION?

Cybersickness continues to become a negative consequence that degrades the interface for users of virtual worlds created for Virtual Reality (VR) users. There are various abnormalities that might cause quantifiable changes in body awareness when donning an Head Mounted Display (HMD) in a Virtual Environment (VE). VR headsets do provide VE that matches the actual world and allows users to have a range of experiences. Motion sickness and simulation sickness performance gives self-report assessments of cybersickness with VEs. In this study a simulator sickness questionnaire is being used to measure the aftereffects of the virtual environment. This research aims to answer if Immersive VR induce cybersickness and impact equilibrium coordination. The present research is formed as a cross-sectional observational analysis. According to the selection criteria, a total of 40 subjects would be recruited from AVBRH, Sawangi Meghe for the research. With intervention being used the experiment lasted 6 months. Simulator sickness questionnaire is used to evaluate the after-effects of a virtual environment. It holds a single period for measuring motion sickness and evaluation of equilibrium tests were done twice at exit and after 10 mins. Virtual reality being used in video games is still in its development. Integrating gameplay action into the VR experience will necessitate a significant amount of study and development. The study has evaluated if Immersive VR induce cybersickness and impact equilibrium coordination. To measure cybersickness, numerous scales have been developed. The essence of cybersickness has been revealed owing to work on motion sickness in a simulated system.
Semi-Supervised Tracking of Multiple Identical Objects With Occlusions

Author(s): Lee, Colin Jiho | Advisor(s): Shelton, Christian R; Roy-Chowdhury, Amit K | Abstract: Recent advances in multiple object tracking (MOT) rely primarily on visual appearance features to reconnect tracks lost due to occlusions. However, appearance features cannot be relied on to discriminate between objects that are visually similar or identical, such as animals, people in uniform, or mass-produced items. We propose a new model that relies on spatio-temporal motion features rather than appearance features for such videos. Furthermore, training an MOT method often relies on expensive hand labeling of bounding boxes or segmentation masks with ground truth tracks. By contrast, our videos are labeled only with fixed bounding boxes (effectively only positional information). We train our model in a semi-supervised manner using iterative pseudo-labeling (IPL), a technique often used in natural language processing, but not common to computer vision tasks. We show that appearance features are insufficient for reconnecting tracklets in videos of bee foraging, and that our motion-based IPL method offers an improvement over appearance feature methods.
Classification of Cervical Cancer in Women Using Convolutional Neural Network

Cervical cancer is regarded as a serious threats to humanity, globally and this is a vital disease with huge spreading of virus that affects the health of humans. The virus is spreading at a rapid rate through mosquitoes that even may kill the one who is affected with cervical cancer. In this paper, we develop a quick response system that certainly finds the disease through a faster validation process. The study uses Convolutional Neural Network (CNN) as a deep learning model that classifies and predicts the condition or the infection status of a patient. The study uses a pre-processing model and a feature extraction model to prepare the image datasets for classification. The simulation is conducted to validate the effectiveness of the model over cervical cancer image datasets i.e. the blood samples of humans. The validation shows that the proposed method effectively classifies the patients in a faster manner than the other deep learning models.
Improving Long Content Question Generation with Multi-level Passage Encoding

Generating questions that can be answered with word spans from passages is an important natural language task, which can be used for educational applications, question-answering systems, and conversational systems. Existing question generation models suffer from creating questions that are often unrelated to the context passage and answer span. In this paper, we first analyze questions generated by a common baseline model: we find over half of the generated questions that are rated as the lowest quality to be semantically unrelated to the context passage. We then investigate how humans ask factual questions and show that most often they are a reformulation of the target sentence and information from context passage. Based on these findings, we propose a multi-level encoding and gated attention fusion based neural network model for question generation (QG) which overcomes these shortcomings. Our experiments demonstrate that our model outperforms existing state-of-art seq2seq QG models.
Procesos de enseñanza mediados por TIC en la Licenciatura en Educación Física de la Universidad de Antioquia

Objective: to inquire about the teaching processes mediated by ICT that have been developed in the Bachelor of Physical Education at the University of Antioquia, between 2000-2020. Method: the data were collected through documentary analysis, survey and interview, through which the experiences of teachers who participated in such processes are delved into. Results: relevant information is obtained on the progress of use, mediation and interaction mediated by ICT to understand its scope in higher education. Conclusion: although teachers have had to be trained in a compulsory and abrupt way in the use of ICT for their work, they have found in these means of great importance for teaching.
Industrial Training Report: Sabah State Library / Elizabeth Zaitol

This industrial training report consists of four (-1) chapters. Chapter l was Introduction which explained the details of Organization Background, History and Services. While, Chapter 2 discussed about the Organization Information that included Division Structure and Functions. Chapter 3 was mainly explained all Industrial Training Activities that the internship students had undergo during the industrial training in every division or department of an organization. Lastly, Chapter 4 discussed the Industrial Training Reflection based on internship students· opinion and experiences during their industrial training. In order to complete study, trainee was required to complete a who!e five months of industrial training which started from 1st of August 2019 until 31st of December 2019. The library that has been selected by trainee was at Sabah State Library Headquarters and Sabah State Library Tanjung Aru Branch. Trainee had done the industrial training for four months and one months at the Tanjung Aru Public Library Branch. During the five months of industrial training, trainee had learnt so much regarding on the management of library. Following the schedule that had been prepared by the organization, trainee had learnt on the improvement of communication skiffs, more discipline and punctual in time management, and most importantly increasing trainee's library skills and knowledge. Industrial training had been a useful experience in practical of library skills in real working environment. Hence, student could be exposed to the real working environment in the future.
A Systematic Literature Review of the Impact of Human Resources Management Strategies on Employee’s Performance: Role of Job Embeddedness and Organizational Commitment as Mediator Variables

The present study seeks to examine the effectiveness of the practices of Human Resources (HR) on the performance of employees.It explores how job embeddedness and organizational commitment can have a mediation effect on the relation between the HR practices and staff's performance.Moreover, this study discusses several dimensions of Human Resources Management System (HRMS) such as recruitment, involvement, performance appraisal, compensation, and training.Furthermore, task performance, the efficiency of work and creativity were taken as dimensions of Employee Performance.Data were collected through questionnaires from the participants.The study's population consisted of 503 employees holding different positions in various sectors.Several results were reached by the study, the most significant of which is the finding that there is a positive relationship between the HRMS and Employee Performance.It was also deduced that an indirect partial mediation effect exists between HRMS and Employee Performance through both job embeddedness and organizational commitment.
Elicitation of nouns based on semantic domains (2)

Recording of an elicitation of the names of household items in Mankiyali based on English words used as prompts. The contributors are Aurangzeb (a 34-year old male teacher) and Gohar-Ur Rehman (a 38-year old male shop owner).
Feature Contours Identification and Mammary Pathologies Detection in Mammography Images

This paper proposes an algorithm for identifying regions of interest by inverse contrast enhancement that provides a representation of the different contours (mass, pectoral muscle, breast outer contour and Mcs). The second contribution is the detection of masses and micro-calcifications by manual thresholding and prewitt detector. This algorithm was tested using mammography images of different densities from multiple databases in a health clinic and images taken from the internet (40 images in total). The results are highly accurate, allowing better identification of the different contours, and better detection of breast pathologies (mass and micro-calcification). Finally, the identification of breast contours was performed using inverse contrast enhancement, which is the input of a manual thresholding algorithm specially designed for this purpose. After segmentation by manual thresholding, morphological opening, morphological dilatation and Prewitt contour detection we have a demarcation of the breast masses and micro-calcification. The results obtained show the robustness of the proposed enhancement and manual thresholding method. In order to evaluate the efficiency of our pathology detector, we performed a qualitative evaluation with a rate of 99% for the identification of the different contours and 98% for the detection of breast pathologies. A radiologist from the health clinic evaluated the results and considered them acceptable for the CAD.
Construction and Application of Teaching Resources Database for Japanese Reading Based on Multimedia Technology

Multimedia teaching is a modern teaching mode in which computer technology is applied to the teaching process. It makes full use of the interactivity, interface friendliness and feedback timeliness of computer to transform the teaching process into an intelligent two-way teaching process. Based on multimedia technology, this paper designs the recording process of micro video and the method of using Apowersoft to record micro video, and designs the core function of Japanese Reading Teaching Resources Database composed of “Web portal, Course information, Teaching material, Teaching resources, Expand resources, Interaction, Background management, System service”. This paper puts forward the application strategy of Japanese reading teaching resources database based on multimedia technology, and points out the advantages and disadvantages of multimedia technology in teaching.
Online disinhibition: Conceptualization, measurement, and implications for online deviant behavior

Online disinhibition is one of the key factors leading to the occurrence of cyberaggression, cyberbullying and various forms of deviant behaviors in the online environment. To understand the composition of online disinhibition, this study aims to conceptualize online disinhibition and develop a measurement instrument for online disinhibition.,We followed a rigorous procedure to develop and validate the multidimensional instrument of online disinhibition in three phases: item generation, measurement development and instrument testing.,We developed a 23-item online disinhibition scale and identified six key dimensions: dissociative anonymity, invisibility, asynchronicity, solipsistic introjections, dissociative imagination and minimization of authority.,The online disinhibition instrument is an accessible and easily administered measure that can be used as a checklist for systems designers and administrators to evaluate the level of online disinhibition among users. It offers systems design information on how to prevent and combat online deviant behaviors on platforms.,This work provides a rich conceptualization of an online disinhibition instrument that can serve as a springboard for future work to understand online deviant behaviors. The newly developed measurement instrument of online disinhibition also adds to the repository of rigorous research scales in this area.
Take Charge of Your Scholarly Narrative: Using Metrics and Altmetrics to Demonstrate Impact

Workshop presented at IU Libraries on November 19, 2019. Access the associated survey at: https://iu.co1.qualtrics.com/jfe/form/SV_5inBA88xqYQo8Qt.
Guides: Virtual Library Research Session: Search Strategies for Databases

Gain a basic understanding of how to use Library research tools through this series of sequenced videos covering keyword development to searching strategies to interlibrary loan. This is a short guide on search strategies for websites and databases.
HATE SPEECH AND HUMAN SOCIETY: A CRITICAL ANALYSIS

This paper critically analyses the concept of ‘hate speech’ and interrogates the possibilities of its impact on human society. The task before the paper is to identify the nuances and underpinning issues that surround the concept and whether it has any socio-political impact. Though the concept of hate speech is regarded as a potential social problem that can cause violence, which poses a threat to mutual co-existence in human society. Nonetheless, in the twenty-first century, the concept has become a topic of discussion globally, as such so many people try to give it a definitional vacuum which is unscientific, it is due to this that this paper uses Raphael’s three models of concept clarification as a theoretical framework to elaborate on the concept and give it a philosophical definitional vacuum. Therefore, using Raphael’s model of analysis, the paper discovers that the concept of hate speech means any form of expression online or offline, spoken or written, which includes images, posters, symbols, memes, emoji , drawings, photographs, and films, etc. which include denying or justifying mass murder, genocide, ethnic cleansing, etc. As such the paper distinguishes hate speech which only targets groups and does not necessarily trigger violent conflict, with an offensive speech that targets individuals and dangerous speech which has all the potentiality of triggering violent conflict. Therefore, from an ethical standpoint, hate speech is an improper use of human communicative prowess because it threatens human relationships, which are the essential ingredient of human society. This paper prescribes that it should be discouraged in human society.