Reviewerly/exHarmony huggingface dataset:
Optical Character Recognition based Webapp

As the use of computers in our daily lives increases, so has the need for a natural procedure to interact with the computers. The ultimate aim of human computer interaction is to bring the change that there is always a natural way of interacting with computers coupled with ease and flexibility. Printed and textual media such as prescriptions, invoices, receipts, etc. occupies a large segment of our day-to-day activities and given their volume, it is inefficient to manage them physically as there’s always an associated risk of fading, damage, misplacing, etc. and hence a medium is required for their digital conversion. In this project, we have developed a robust, cross-platform web application that can process the images using PyTesseract based algorithms that can efficiently extract the textual data to facilitate the storage and retrieval of the same. The extracted text can be downloaded as a text file and can also be translated into the desired language. This is an active field of research and thus this paper also discusses various current implementations of the mentioned concept. The Optical Character Recognition framework finds applications in a variety of fields such as business process activities, number plate recognition, KYC and banking processes to name a few.
Data Compression and Encryption for Remote Sensor Networks Using Different Techniques Methods

Wireless sensor networks (WSNs) are widely used for the different multimedia applications in which the data in multimedia form (e.g., images and videos) are captured by visual sensors and transmitted to base stations or destination nodes, and such networks, commonly called wireless multimedia sensor networks (WMSN), transmit high-quality images over sensor nodes with image quality improvement and CS technique while the security of CS data is achieved. The one-way DF-based cooperative digital image transmission model over WSNs using advanced terminologies for image compression called advanced JPEG2000 compression and modified elliptical curve cryptography (ECC) encryption is proposed. Image quality improvement efficiency is essential in multimedia applications and wireless communications. The authors proposed a novel technique based on adaptive and dynamic noise removal and quality improvement for both before compression and after compression. The compression method designed is based on CS technique.
A Critical Appraisal of Ethical issues in E-Learning

Covid-19 pandemic left a long lasting impact on entire education sector, as an estimated 90% of educational institutions closed down in at least 188 countries in the world and offline traditional teaching came to a standstill. In such critical situation pedagogical innovations in form of online education, virtual simulators etc came to rescue to keep the students academically occupied and motivated entering into the virtual era.With advent of online education, several issues like social, infrastructural &amp; pedagogical and psychological issues came to fore. Social divide, geographical issues, technical support and know how etc added to the gravity of situation. Educationists also pointed out that ethical issues in e-learning like academic dishonesty, plagiarism and copyright violations need to be addressed.The present work is an attempt to find out various ethical issues in online education and to make suggestions, where ever required.
Assessing The Actors’ Readiness To Educational Cooperation In The Age Of Digitalization

In this study, the authors proposed a model of the educational ecosystem, reflecting current trends in digital transformation.The described model of the educational ecosystem includes the types of actors of the university ecosystem and the external environment.Biotic and abiotic interactions occurring in the physical and digital space are divided into symbiotic, competitive and parasitic ones.There are proposed the most promising technologies, software and services for the selected types of interactions.These technologies can contribute to the effective transition of universities to a higher level of digital transformation.The model of digital educational environment (DLE) architecture, based on a service-oriented approach (SOA) is proposed.The applied part of this article presents the results of assessing the actors' readiness in educational process to use the DLE tools at present.We conducted the online survey to identify students' preferences and their self-assessment of working skills in a digital environment.The online testing made it possible to assess the ability for communication in a digital area, skills of making digital content, providing digital security, solving problems in a digital environment.As a result, we found out in which areas actors are most prepared for digital interaction.In the research is revealed whether there are "significant" gender differences, and whether the chosen "field of study" (technical, humanitarian, economic) affects the level of digital competencies.
PENGUATAN KARAKTER REMAJA MENGGUNAKAN MEDIA WAYANG CAKRIK BATIK

The popularity of puppets and batik in the eyes of teenagers, especially Javanese people, is already inferior to fictional Hollywood superhero figures such as Hulk, Superman, Batman, Ironman, Spiderman, and other Avenger. On the other hand, we actually have a wealth of traditional art forms that are very rich in philosophical values and unmatched artistic techniques. However, nowadays, youth's pride in the nation's art works seems fragile and easily outdated, being replaced by an external art culture that is full of modernity and relatively superficial in value. The redesign of the wayang cakrik batik from the wayang kulit reference object is an effort to strengthen the national identity of the youth, while at the same time offering a solution so that the youth will love and be proud of the art of their ancestral heritage. This survey research with a quantitative descriptive approach seeks to evaluate and capture the responses of adolescents as the main target audience regarding the redesign of this batik cakrik puppet so that it fosters the enthusiasm of the teenagers. As a result, the teenagers received well the works of wayang cakrik batik from various aspects that were important to observe, namely mainly with the visual communication design approach. A process that is no less important after this research is the development and refinement of the redesign of the batik cakrik wayang by considering the audience's response.
Unpredefined ball detection algorithm for humanoid soccer robots

Humanoid soccer robots need to adapt to the conditions in human soccer games such as detecting a soccer ball that does not have predefined characteristics such as a definite color and that may blend in with the playing field. For such conditions, the problem cannot be solved by classical detection strategies based on a single colorblock. In this study, the ball color is split into a specific color and a shared color. Two rounds of labelling are used to generate a color lookup table. Color-blocks obtained by pixel-level segmentation are used in a marco-pixel clustering method based on a connecting relationship graph to generate several ball candidates. The best ball object is estimated via the membership function by fuzzy logic. Tests show that the method is able to detect unpredefined balls even in a very disturbed environment and at large distances from the robot and is also able to avoid confusion with the border lines and other robots on the field without excessive computing requirements. The calculations can reach a high framerate of 15 frames per second. This strategy provides an efficient detection method using strictly limited computing resources for robot soccer players. 摘要 为适应人类赛场环境, 仿人足球机器人需能够识别未预先定义足球, 此时足球不再具有固定的与场地鲜明对比的颜色, 因而不能通过传统的单色块识别策略解决。该文将足球颜色划分为专有色和共有色两类, 采用两轮颜色标记方法生成颜色查找表; 在图像像素级联通分割获得色块的基础上, 提出基于图连接关系的宏像素聚类算法, 从而得到若干足球识别候选对象; 再利用模糊逻辑方法中的隶属度函数从候选对象中获得最佳足球识别结果。实验表明在不具备高性能计算硬件平台的情况下, 算法能够在存在大量干扰, 远近距离大幅度变化的条件下准确识别出非预先定义的足球, 避免与边线、机器人等对象的混淆, 且达到每秒15帧的计算速率。该算法能够在严格受限的计算能力下达到高效的足球识别能力, 从而为参赛机器人提供了一种崭新策略。
Aplikasi Penerjemah Bahasa Isyarat Indonesia menjadi Suara berbasis Android menggunakan Tensorflow

Indonesian Sign Language or BISINDO is a two-handed sign language that is used as a liaison in communication. BISINDO is used by people who have limited speech or hearing, but not for other communities. This causes BISINDO users have difficulties in conveying information because only a few people understand BISINDO. Therefore, an application was developed to help communication between BISINDO users and Indonesian in realtime. BISINDO classification is carried out using the Convolutional Neural Network method and the MobilenetV2 architecture using tensorflow. The classification results are used as a model for android which is then used as a sound. Based on model testing, the resulting accuracy rate resulted in 54.8% in the classification of 30 specified languages. Thus, the performance of the model can be said to be not optimal in classifying. Based on the application testers to 30% of respondents, it was found that respondents strongly agreed with this application with an average value of 83.95%.
STRUKTUR DAN UNSUR KEBAHASAAN TEKS DESKRIPSI SISWA KELAS VII SMP NEGERI 30 PADANG

ABSTRACT This research was conducted to describe the structure and linguistic elements of the description text of class VII students of SMP Negeri 30 Padang. This type of research is qualitative with descriptive method. The data of this study are qualitative data in the form of structure and linguistic elements of the student's description text. The data are analyzed by steps, namely (1) the researcher identifies the general elements contained in the description text, (2) analyzes the essay based on the aspects studied, namely the structure and linguistic elements of the student's description text, (3) the results of the analysis the researcher examined by triangulation informants, (4) make conclusions. Based on the results of the study, two things are summarized as follows. First, in writing the description text the seventh grade students of Padang Public Middle School 30 have used both text structures. The two text structures are identification/general description and description of parts. This is evident from the 40 description texts that have been analyzed, there are 39 complete description texts using identification/general description and part descriptions. Second, in terms of language, the seventh grade students of Padang Public Middle School 30 still have errors. This is evident from the 422 sentences analyzed, there were 281 sentences and the EBI was incorrect. Kata kunci: Struktur Teks, Unsur Kebahasaan, Teks Deskripsi
Image Inpainting Using Image Interpolation - An Analysis

Image inpainting is a computer technique of filling lost regions of an image by using available information from the surrounding area. This digital image inpainting technique has wider applications like image restoration, dis-occlusion and image/video compression. The traditional image inpainting approaches Partial Differential Equation (PDE) based method and Exemplar based method mainly focus on the size of the target region to be filled. PDE is a pixel oriented method and works well if the region to be filled is small. On the other hand exemplar based method is a patch based method and works well if the region to be filled is large. This paper proposes another new technique called image interpolation technique and describes how this technique can be used effectively for image inpainting without giving much focus on the size of the target region.
Multi-method experience sampling in information behaviour research

Capturing information behaviours and attitudes that occur in natural settings is a challenge. Observational methods are often intrusive or retrospective proxies, which may change behaviour or misrepresent attitudes. Technology enables novel approaches to in-situ quantitative data collection but rarely explores qualitative reflections; informing researchers on what happened, but not necessarily why. Recent work uses multi-method approaches that combine quantitative data, tracking experiences, feelings, and behaviours over time, with qualitative data to gain deeper insights into subjective experiences. This paper introduces information and library scientists to a multi-method approach to the data collection of subjective experiences over time.
UPDATED CONTENT OF EDUCATION IN TERMS OF CRITERIA-BASED ASSESSMENT OF STUDENTS ' EDUCATIONAL ACHIEVEMENTS

This scientific article discusses the assessment as a necessary component of the educational process, which is information about the progress of students at the current and final stages of training. The authors show the possibility of using the criterion approach by future teachers in the professional evaluation of educational activities of students. In accordance with this, on the basis of the shown necessary professional competencies of future specialists, an attempt is made to develop and present criteria for assessing the quality of the educational process. The components, main tasks and advantages of criteria evaluation are revealed
The Technology of Competencies Acquisition by Bachelors in Higher Education Institutions in the Conditions of the Digital Media Communication Environment

This paper describes the technology of competencies acquisition by bachelors in higher education institutions in the conditions of the digital media communication environment.The use of media communication technologies requires an adequate level of acquisition of professional competencies by higher education applicants.The services that can be obtained in the process of preparation of higher education applicants through LMS based digital platforms + Office 365 are considered.The results provided an opportunity to outline digital media communication technologies for the acquisition of professional competencies by higher education applicants based on the use of the modern educational platform Cloud365 and the logical and harmonious combination of LMS + Office 365, which provides for the integration of modern systems, interactive tools, video and audio training.The technology of creation of the repository of competencies, the system of their coding and the leading principles of the development of a set of tasks for forming the professional competences of bachelors in the field of electrical engineering are considered.The effectiveness of the proposed technology was tested using the Kolmogorov-Smirnov statistical criterion.
Online 3D path planning for Tri-copter drone using GWO-IBA algorithm

Robots at present are involved in many parts of life, especially mobile robots, which are two parts, ground robots and flying robots, and the best example of a flying robot is the drone. Path planning is a fundamental part of UAVs because the drone follows the path that leads it to goal with obstacle avoidance. Therefore, this paper proposes a hybrid algorithm (grey wolf optimization - intelligent bug algorithm GWO-IBA) to determine the best, shortest and without obstacles path. The hybrid algorithm was implemented and tested in the MATLAB program on the Tri-copter model, and it gave different paths in different environments. The paths obtained were characterized by being free of obstacles and the shortest paths available to reach the target.
Estimation of Uncertainty Bounds on Disparate Treatment when using Proxies for the Protected Attribute

This paper proposes a new method for uncovering discrimination in decision making systems with continuous value outcomes when lacking the protected attribute values.We demonstrate our method over race discrimination using name and surname proxies.Also, we use a new method for estimating uncertainty in the disparate treatment evaluation to allow for better judgment when using imprecise proxies for the protected attribute.We carry out tests using synthetic data.
Proposed Model For Artificial Intelligence Acceptance in Recruitment: Telecom in Jordan

Organizations often aim to conveniently and rapidly provide their clients with a competitive value, so many organizations have taken advantage of the enormous technology and communications growth and introduced their services electronically and switched from 'traditional management' to 'electronic management.' In this context, HRM was designed to be EHRM, and the implementation of AI in the HRM is being presented at the time of the digital world. However, many organizations still have difficulties, particularly in developed countries, regarding the level of consumer acceptance of these services. There is still little awareness of user recognition of the use of AI in HRM services. In addition to this, previous literature research on the adoption of AI in HRM was mainly performed in developing countries. This study's primary objective was to provide a theoretical discussion and propose a theoretical framework for adapting HRM AI in the telecom sector in a developing country such as Jordan. Also, it addresses the variables that may influence the level of acceptance of the extended UTAUT2 model and describes the variables that affect the level of acceptance.
Position Encoding Schemes for Linear Aggregation of Word Sequences

Deep Averaging Networks (DANs) show strong performance in several key Natural Language Processing (NLP) tasks.However, their chief drawback is not accounting for the position of tokens when encoding sequences.We study how existing position encodings might be integrated into the DAN architecture.In addition, we propose a novel position encoding built specifically for DANs, which allows greater generalization capabilities to unseen lengths of sequences.This is demonstrated on decision tasks on binary sequences.Further, the resulting architecture is compared against unordered aggregation on sentiment analysis both with word-and character-level tokenization, to mixed results.
A Fast and Accurate System for Face Mask Detection in Public Places

Changes in the way of life of everybody around the world. In those progressions wearing a cover has been indispensable to each person. Location of individuals who are not wearing veils is a test because of Outbreak of the Coronavirus pandemic has made different the enormous number of populaces. The COVID-19 pandemic has reshaped life. Numerous of us are remaining at home, staying away from individuals in the city and changing every day propensities, such as going to class or work, in manners we never envisioned. While we are changing old practices, there are new schedules we need to receive. Most importantly is the propensity for wearing a veil or face covering at whatever point we are in a public space. Veils and face covers can forestall the wearer from communicating the COVID-19 infection to other people and may give some assurance to the wearer. All-inclusive cover use can altogether diminish infection transmission locally by forestalling anybody, including the individuals who are accidentally conveying the infection, from communicating it to other people. Along these lines, the significance of wearing veil and its identification is exceptionally clear. Face veil recognition frameworks are currently progressively significant, particularly in keen medical clinics for viable patient consideration. They're likewise significant in arenas, air terminals, stockrooms, and other swarmed spaces where pedestrian activity is weighty and security guidelines are basic to defending everybody's wellbeing. Face veil recognition framework can guarantee our security and the security of others. This task can be utilized in schools, clinics, banks, air terminals, and so forth as a digitized examining instrument. The procedure of recognizing individuals' countenances and isolating them into two classes in particular individuals with covers and individuals without covers is finished with the assistance of picture handling and profound learning. With the assistance of this task, an individual who is expected to screen individuals can be situated in a far off region furthermore, still can screen productively and give directions appropriately. Different libraries of python like Open CV, Tensor Flow and Keras are utilized. In Deep Learning Convolution Neural Networks is a class Deep Neural Networks which is used to prepare the models in this task.
SYSTEM OF IMAGE RECOGNITION OF SURROUNDING OBJECTS WITH NEURAL NETWORKS

The article considers one of the directions of automation of recognition of real world objects using the convolutional neural networks.The recognition of objects in an image and their classification is the basis of machine vision systems.However, real-world computer recognition systems do not always work well.The main problem is that in most cases it is not possible to properly identify the features on which recognition should be based.For tasks where such features can be identified, artificial recognition systems have become widespread and widely used.For example, recognition of vehicle license plates, human faces, etc.However, sufficient adequacy of selection and recognition of various objects of the real world in the time close to the real one is still not achieved, which does not allow to achieve the necessary indicators in real tasks.Purpose of research is the development of an efficient neural network algorithm capable of quickly and accurately recognizing real-world objects containing images from a predetermined list of objects.Method.basised on the analysis of algorithms and neural network architecture, the most appropriate type of neural network was chosen; the algorithm of object recognition in the image was optimized; the most suitable configuration of hyperparameterizations of neural networks was empirically chosen, directly influences the speed and performance of the neural network in recognition.Results.Several models have been developed for neural networks, such as precise, precise2, and fast, with specific hyperparameter configurations.Then the neural network was trained on the basis of these configurations with the COCO dataset and the main functions of the created system were tested.Scientific novelty is the development of an advanced algorithm for the recognition of objects and their borders on the image.Practical importance.A system has been developed that can quickly and accurately recognize and mark objects in an image.The system can also work with any data set and is very flexible in setting.
Job Crafting and Employees’ Performance in MTN Nigeria PLC

This study examines the relationship between job crafting (task crafting and relational crafting) and employees' performance (employees’ task performance and organizational citizen behavior) amongst staff of MTN Nigeria PLC. This research makes use of a survey design and analysis was based on primary data generated through a structured questionnaire. Two research hypotheses were formulated and tested at 0.05 levels of significance. The findings revealed that there was a statistically significant influence of task crafting on employees’ task performance in MTN Nigeria, PLC (R2=0.088, F=17.844, p&lt;0.050). Similarly, there is a significant positive relationship between relational crafting and organizational citizenship behavior (rp=0.331, n=187, p&lt;0.050). From the study, it was concluded that workers require a high degree of autonomy and independence on their jobs to perform more efficiently and effectively in order to improve their performance. It was recommended amongst others that organization should provide a flexible job design and structure as well as interpersonal relationship for its employees’ so as to enable them to better perform on the task and create organizational citizen behavior among the employees. Keywords: employees’ performance, job crafting, relational crafting, organizational citizen behavior