Reviewerly/exHarmony huggingface dataset:
Sentimental Analysis using Machine Learning and Deep Learning: Performance Measurement, Challenges and Opportunities

Our regular existence has consistently been impacted with the aid of what individuals think. Thoughts and tests of others have consistently inspired our personal sentiments. Web 2.0 has caused extended action in Podcasting, Tagging, Blogging, and Social Networking. As an end result, social media web sites have emerged as one of the structures to raise consumer’s opinions and influence the way any commercial enterprise is commercialized. Sentiment analysis is the prediction of feelings in a word, sentence, or corpus of files. It is deliberate to fill in as a software to recognize the mentalities, conclusions, and feelings communicated interior a web point out. This paper reviews at the design of sentiment evaluation, mining the sizeable resources of information for evaluations. The number one goal is to provide a way for studying sentiment rating in social media platforms. Here we discuss diverse methods to perform a computational remedy of sentiments and reviews, diverse supervised or facts-driven techniques to research sentiments like Naïve Bayes, Support Vector Machine, and SentiWordNet technique to Sentiment Analysis. Results classify consumer’s belief through social media posts into positive, negative, and neutral.
Ethical and pedagogical aspects of the historical development of domestic social and pedagogical thought in the context of pedagogical morality

Ethical and pedagogical aspects of the historical development of domestic social and pedagogical thought in the context of pedagogical morality
The Use of “English Tenses Practice” Application in Mobile Phone to Improve the Tenth Grade Students’ Mastery of Past Tense and Present Perfect Tense at Senior High School

This classroom action research aimed to improve the tenth grade students’ mastery of past tense and present perfect tense by using “English Tenses Practice” application and to know how the application improve the students participation during the teaching and learning process. The research participants were the X MIPA 3 students which were chosen purposively based on the students’ previous English main score. The data were collected by using grammar post-test and observation in the teaching and learning process of grammar. Then, the collected data were analyzed using descriptive statistic to know how the students’ grammar mastery and their active participation after given an action. The results of the analysis showed that the use of “English Tenses Practice” application could improve the students’ grammar mastery of past tense and present perfect tense and their participation after given an action in the first cycle. It is suggested for English teacher that “English Tenses Practice” application on mobile phone can be used as the medium in the teaching and learning process of grammar.
Spectral Pre-Adaptation for Restoring Real-World Blurred Images using Standard Deconvolution Methods

Classical blur models are based on simplifying assumptions, namely shift-equivariance and circular boundary condition (CBC), that rarely hold in practice.Shift-equivariance means that a shift of the input produces the same shift of the output, which implies that blur is spatially invariant and image aliasing is not present.The CBC assumes that the image is rectangular and periodically repeating.Discrepancies between simplified models and real blurred observations cause strong artifacts in image restoration.The common remedy is to increase the model complexity and remove simplifying assumptions.However, this also brings extra computational complexity to the restoration task.We present spectral pre-adaptation (SPA) that pre-processes blurred images so they can be restored using fast standard deconvolution algorithms suitable for simplified models.The SPA serves as a connector between classical deconvolution methods and a variety of real observations involving blur.Experiments on simulated and real images show that standard deconvolution of SPA-interpolated images not only greatly reduces artifacts compared to direct deconvolution, but performs on a par with more complex restoration methods.
Learning-based three-dimensional registration with weak bounding box supervision

Purpose: Image registration is the process of aligning images, and it is a fundamental task in medical image analysis. While many tasks in the field of image analysis, such as image segmentation, are handled almost entirely with deep learning and exceed the accuracy of conventional algorithms, currently available deformable image registration methods are often still conventional. Deep learning methods for medical image registration have recently reached the accuracy of conventional algorithms. However, they are often based on a weakly supervised learning scheme using multilabel image segmentations during training. The creation of such detailed annotations is very time-consuming. Approach: We propose a weakly supervised learning scheme for deformable image registration. By calculating the loss function based on only bounding box labels, we are able to train an image registration network for large displacement deformations without using densely labeled images. We evaluate our model on interpatient three-dimensional abdominal CT and MRI images. Results: The results show an improvement of ∼10 % (for CT images) and 20% (for MRI images) in comparison to the unsupervised method. When taking into account the reduced annotation effort, the performance also exceeds the performance of weakly supervised training using detailed image segmentations. Conclusion: We show that the performance of image registration methods can be enhanced with little annotation effort using our proposed method.
Towards dealing with commonly occurring requirements engineering process issues during software development outsourcing

Due to specific advantages, the volume of Software Development Outsourcing (SDO) is rapidly increasing. Because of challenges arising from the Requirements Engineering (RE) process, the anticipated benefits of SDO are not achieved in case of several projects. The objective of this research work is to recommend RE practices for addressing the commonly arising RE process issues in the case of SDO. For this reason, a thorough literature review has been undertaken, as well as two questionnaire surveys have been performed with skilled SDO industry practitioners. The surveys have been done by utilizing semi-supervised style and employing Convenience Sampling method. The 50 percent rule and a four-point Likert Scale have also been used to determine the advantages of RE practices for dealing with the issues. A comprehensive list of 147 RE practices has been extracted by conducting a Focus Group session. Furthermore, the 147 RE practices have been ranked by applying Numerical Assignment and Hundred Dollar Techniques during two Focus Group sessions. The detection and adaptation of RE practices aids in enhancing the SDO RE process, evading SDO failures, and achieving the associated SDO advantages.
Self-Supervised Sidewalk Perception Using Fast Video Semantic Segmentation for Robotic Wheelchairs in Smart Mobility

The real-time segmentation of sidewalk environments is critical to achieving autonomous navigation for robotic wheelchairs in urban territories. A robust and real-time video semantic segmentation offers an apt solution for advanced visual perception in such complex domains. The key to this proposition is to have a method with lightweight flow estimations and reliable feature extractions. We address this by selecting an approach based on recent trends in video segmentation. Although these approaches demonstrate efficient and cost-effective segmentation performance in cross-domain implementations, they require additional procedures to put their striking characteristics into practical use. We use our method for developing a visual perception technique to perform in urban sidewalk environments for the robotic wheelchair. We generate a collection of synthetic scenes in a blending target distribution to train and validate our approach. Experimental results show that our method improves prediction accuracy on our benchmark with tolerable loss of speed and without additional overhead. Overall, our technique serves as a reference to transfer and develop perception algorithms for any cross-domain visual perception applications with less downtime.
Cyto-Histopathological Correlations in Pathology Diagnostics

Cyto-histopathological correlation is a key player in measuring quality in a quality programme [...]
Inference Acceleration with Adaptive Distributed DNN Partition over Dynamic Video Stream

Deep neural network-based computer vision applications have exploded and are widely used in intelligent services for IoT devices. Due to the computationally intensive nature of DNNs, the deployment and execution of intelligent applications in smart scenarios face the challenge of limited device resources. Existing job scheduling strategies are single-focused and have limited support for large-scale end-device scenarios. In this paper, we present ADDP, an adaptive distributed DNN partition method that supports video analysis on large-scale smart cameras. ADDP applies to the commonly used DNN models for computer vision and contains a feature-map layer partition module (FLP) supporting edge-to-end collaborative model partition and a feature-map size partition (FSP) module supporting multidevice parallel inference. Based on the inference delay minimization objective, FLP and FSP achieve a tradeoff between the arithmetic and communication resources of different devices. We validate ADDP on heterogeneous devices and show that both the FLP module and the FSP module outperform existing approaches and reduce single-frame response latency by 10–25% compared to the pure on-device processing.
Lithuanisation of Software Metaphors

The majority of software that is localised, i.e., adapted or Lithuanised as a product to the Lithuanian market, language, culture, social norms and values, is originally engineered and designed in the United States of America. Despite the fact that internationalisation has to be carried out as a process of neutralising and standardising the software for further localisation of the product, it is usually carried out incompletely or in some cases might be unperformed at all, if companies have not considered the product to be sold globally. Thus, the software contains attributes, for example, writing conventions, legal norms and rules, culture-specific items, metaphors and other that reflect the source culture and language of the software. Software related texts, online help documents, resource files, messages and other contain various metaphors that are related to applications, malfunctioning, software components and menu items and hardware. At the same time, conceptual metaphors represent the worldview, and its perception is pertinent only to some specific language users. The idea of localisation is both to adapt products to target users in terms of their culture and language and make them feel that the product was designed and created for them. Thus, taking in mind that conceptual metaphors represent the perception of the worldview, the crucial question arises, if it is possible to adapt, i.e., Lithuanise, conceptual metaphors to such an extent that they would reflect the worldview and perception of the target language and culture the tropes are used to represent, categorise and depict. At the same time, it becomes interesting to examine how the trope is being changed in the target language as well as analyse the capacities of the language to change, adapt to and embrace new things it has to name.
Infracción a la propiedad intelectual en una plataforma de e-commerce: análisis de la responsabilidad del portal de ventas

One of the most controversial points in relation to the legal consequences derived from the role of intermediaries exercised by digital platforms is found in determining the scope of their responsibility. In Argentina, in the event of an infringement of intellectual property produced within the scope of the platform, it is assumed that there is no specific regulation on the responsibility of the latter. As a result of the aforementioned ruling, the CNCivil had in its hands a new opportunity to pronounce itself on the matter – this time, due to an infringement of intellectual property within Mercado Libre – and, specifically, the emergence of the question of whether it should respond for the publication and/or marketing of a plagiarized book on its online sales site. Thus, attentive to the circumstances of the case and making a realistic assessment of the concrete possibilities of knowing the wrongful act in advance by Mercado Libre, the Chamber considered that the most equitable thing was to judge its responsibility through the application of the "subjective" doctrine and , due to the fact that a priori knowledge of plagiarism had not been invoked or accredited in the judicial process, consequently, it decided not to file the lawsuit against the renowned platform.
A novel term weighting scheme for imbalanced text classification

High dimensional feature is the main problem of text domain. If imbalance class is also found in the context, the classifier’s performance is worsen. Moreover, solving imbalance problem by oversampling method in this circumstance is very difficult to get performance improvement. In this paper, a new term weighting scheme is proposed by combining Term frequency with an average of inverse document frequency factor. We denoted our scheme by TFmeanIDF. Our proposed method has high potential for imbalance text domain with high dimension. No feature selection or oversampling method is required. Extensive comparison results on 7 datasets validate the advantages of TFmeanIDF in terms of F1 score obtained from widely used base classifier such as logistic regression and Support Vector Machines. We found that F1 score of minority class is higher than that of baseline term weighting schemes. Using TFmeanIDF as a term weighting shows promising result of logistic regression and Support Vector Machines.
Methods of teaching and evaluation of learning outcomes in the discipline «Pedagogical skills»

In this article, the authors reveal the content of pedagogical skill, its elements. The authors pay special attention to the formation of pedagogical skills among future teachers based on modern technologies, methods of teaching, and upbringing, which can be considered an ideal of pedagogical activity thatencourages teachers to self-improvement and a standard that includes an assessment of the effectivenessof pedagogical work.Pedagogical excellence implies such professional qualities that take into account and recognize theindividuality, uniqueness of the student’s personality, allow him to build the process of education andupbringing in such a way as to provide students with the maximum favorable conditions for revealingtheir creative potential, creativity and the best characterological features of the individual.Pedagogical skills of teachers, expressed in a combination of individual human and professionalqualities, love for their work – conditions for the formation of the personality of a future specialist. Thecomponents of pedagogical skills are considered considering the individual approach of action, the formation of the main structures of the teacher’s personality, and methods of pedagogical influence.Implementing current education policies is impossible without a teacher with high professionalism, creative potential, and leading academic positions in society. A modern teacher, working with theintellectual saturation of the content of Education, a high level of teaching methods, strives to know,love, and help university students to create themselves, thinks about the degree of participation in themodernization and development of the University.The pedagogical activity contributes to the implementation of social continuity of generations, including young people in the system of social contacts. It helps to realize the natural capabilities of aperson in mastering social experience. Key words: Pedagogical skills, pedagogical techniques, pedagogical competence, learning achievements, tools for assessment and measurement, nanotechnology.
Peculiarities of Teaching Biology in Universities under Conditions of Digitalization

Currently, all areas of society are moving toward the mass use of information systems and technologies. Many countries are introducing information systems into the educational process. Every modernteacher should be fluent in information technology. In this way, it helps to increase student motivationfor the class. Changing the system of relations between the teacher and the student, the content, thestructure of their activities, they affect their motivational emotional environment. The use of informationand technological means allows you to turn the biology lesson into a fascinating and productive lesson.The article considers effective methods of using electronic educational resources and capabilities ofeducational platforms in the conditions of transition to distance learning in accordance with the requirements of the state program “Digital Kazakhstan”. It is emphasized that when teaching students, it is important to use effective modern methods and techniques, as well as visual and auditory elements insteadof methods and approaches that make students dependent on the textbook and limit them to what theteacher teaches. The effectiveness of using videos in biology classes was studied. Student performanceresults are given on the research paper. In particular, the use of video materials during classes allowsstudents to convey the necessary information as accurately as possible, and students, due to their modern capabilities and features, better absorb the material in this way. The results of questionnaires fromdifferent regions on the effectiveness of videos were discussed and analyzed. Thus, the study revealedthe necessity of using videos in biology lessons to facilitate students’ learning and their effectiveness inthe learning process.Key words: information technology, methods, videos, experimental, control, performance,creativity.
Digital Educational Resources as Ensuring a New Quality of Education

The article considers the possibilities of a digital educational platform developed and partially prepared by a group of scientists within the framework of the scientific project of the KN of the Ministry ofEducation and Science of the Republic of Kazakhstan “Creating digital content for methodological support of Kazakh rural teachers of Russian language and literature in the organization of the educationalprocess in a remote format”. Educational content is located at: https://auyl-school.kz/The authors are currently working on the creation of digital educational resources to help teachers of the Russian language and literature of Kazakh schools, the content of which is completely tiedto the Standard curriculum on the subject “Russian language and Literature”. The developed tasks canbe applied by teachers in their lessons and the digital educational resources compiled for the primaryschool meet modern educational needs, contain video tutorials and audio materials, tests, presentations,simulators – collections of interactive tasks with automatic response verification, educational and methodological materials that a teacher can use to design online lessons and build effective interaction andorganization of students’ work in a digital environment.The authors believe that the use of digital educational resources is justified, as it allows students toactivate their activities, makes it possible to improve the quality of education, improve the professionallevel of a teacher, and diversify the forms of communication of all participants in the educational process.Key words: Russian language and literature, digital educational resource, educational content, interactive tasks.
Application of Fuzzy C-Means and Weighted Scoring Methods for Mapping Blankspot Villages in Pemalang Regency

Covid-19 pandemic affects habits people around the world. The education sector in Indonesia is also undergoing policy changes, namely policy of transitioning face-to-face teaching and learning process to distance learning process (PJJ/online learning). Several studies have been conducted to examine the constraints PJJ process, resulting in finding that quality of internet network is majority obstacle in PJJ process. Conditions where there is no internet network in an area is commonly called a blankspot. In order to minimize the problem of blankspots, President and Ministry of Communication and Informatics of Indonesia realized the program "Indonesia is free signals to the corners of the country". This program involves all districts in Indonesia to conduct network quality surveys in the smallest areas of the village. Basically, network quality survey activities require relatively no small resources and costs. So as to conduct the efficiency of field survey activities, early detection of village blankspot status is required based on the characteristics blankspot village in general. While the commonly used method of grouping village based on village characteristics is the fuzzy c-means and weighted scoring method. These two methods were chosen because they have good cluster convergence rate and easily interpreted display results of the group by user in the form diagrams and scores. This study aims to prove that fuzzy c-means and weighted scoring method are good for grouping cases of blankspot villages according to previous studies with different cases. The result comparison goodness value of clustering, it is known that fuzzy c-means method more suitable for clustering characteristics blankspot village than the k-means method. Meanwhile, weighted scoring method cannot be said better method for village classification than the decision tree method.