Reviewerly/exHarmony huggingface dataset:
For One Type Of Zig-Zag Thematic Structure In Voip Conversationwith Viber App

In large number of social media and mobile applications, a new hybrid oral-writing formation is emerging, which is called from linguists written spoken speech with similar features to both written and oral speech, but also having its own distinctive features.This study will illustrate the thematic structure of a conversation using the VoIP application Viber to highlight the most common model of a zig-zag themed organization and its specifics.The results of the analysis show that in the fragmented arrangement of the topics, in the frequent insertion of new topics, the conversation through Viber is closer to the oral conversation. The zig-zag thematic structuring model is so widespread that the application provided a technological tool to recall an earlier cue, which was replied with a delay as new topics came into the conversation. Understanding the specifics of written conversational speech optimizes real-time communicationapplications to eliminate or at least reduce communication noise through the Viber VoIP application.
О проблемах обучения программированию дистанционно

The article discusses the experience of developing and using a distance course within the framework of studying the courses “Programming” and “Operating Systems” for students of the Faculty of Applied Mathematics and Computer Science of the Belarusian State University (specialties “Computer Security”, “Economical Cybernetics” and “Actuarial Mathematics”). The features of development and work with a distance course are highlighted both for the teacher and for students. The positive aspects of this form of work and the difficulties associated with it are evaluated
GC-MRNet: Gated Cascade Multi-stage Regression Network for Crowd Counting

Crowd counting is a challenging task due to occlusions, continuous scale variation of target and perspective distortion. The existing density-based approaches usually utilize deep convolutional neural network (CNN) to regress a density map from deep level features and obtained the counts. However, the best results may be obtained from the features of lower level instead of deep level. It is mainly due to the overfitting that degrades the adaptability towards the continuous scale variation of target. To address the issue of overfitting, a novel approach, called gated cascade multi-stage regression network (GC-MRNet), was proposed. It aims to maintain the adaptability towards scale variation of target and generate higher accuracy estimated density maps. Firstly, the dense scale network (DSNet) was used as the backbone and multi-stage regression was employed to achieve different density map regressors in different levels. Then, the features derived from the density map were cascaded to assist generating a higher quality density map in next stage. Finally, the gated blocks were designed to achieve the controllable information interaction between cascade and backbone. Extensive experiments were conducted on the ShanghaiTech, UCF-QNRF and UCF-CC-50 datasets. The results demonstrated significant improvements of GC-MRNet, almost over the state-of-the-art on ShanghaiTech Part A.
LibGuides: Library Induction: Distance Student Support

A hub for everything you need to be introduced to the library. Click on the menu to explore further.
Deploy and Host Services Using Containers

Well, if you have not heard of containers, you might still be using dial-up Internet! Let’s just say that containers are the best thing since sliced bread. Containers enable you to deploy your software in a consistent and repeatable manner, in multiple environments. They are not as nearly as bulky as VMs. Scott Hanselman, Microsoft explainer in chief, has done an excellent video on containers, which I can’t recommend enough, especially if you are new to this container ecosystem.
Denoising, Edge Aware Restoration and Enhancement of Single Shallow Coastal Water Image

The dissolved particles and their resultant scattering are the underlying cause of low contrast and blur thereby producing poor quality underwater images. Single-shot shallow coastal underwater images are much in need of the preprocessing steps viz. image enhancement and restoration. The underwater image processing operations like classification, object detection and computer vision require an enhancement/restoration preprocessing. The paper aims to restore the visibility of objects in turbid water images with its effective edge aware restoration cum enhancement model. The restricted rolling guidance filter on the DCP-based restoration method produces better edge aware restoration and denoised output image. The model-based (MB) dark channel prior (DCP) along with an edge emphasis and contrast enhancement achieves the essential dehazing and improvement in contrast for the heavily blurred underwater images. The subjective and objective projections are an evidence for the same. This edge preserving and denoising nature of the model is also exhibited with comparisons made with promising algorithms over the decade.
Kepuasan siswa sekolah dasar terhadap pembelajaran daring di tengah pandemi COVID-19

The purpose of this study was to identify information about the satisfaction of teaching and learning online at home due to the Covid-19 pandemic. The research method used is the survey method, with the instrument used is a questionnaire through a Google form that is distributed to elementary school students. In this study, respondents were elementary school students in the city of Surabaya. Word has circulated that online learning is less effective, because there is no maximum preparation in terms of regulation, field implementation and also students, as well as supporting infrastructure for online learning, therefore researchers have a desire to test the satisfaction level of online learning. Because there can be no learning content lost in the middle of this pandemic. The results of this study there are several obstacles experienced by students, teachers and parents in online learning activities, namely lack of technology mastery, additional internet quota fees, additional work for parents in assisting children's learning, communication and socialization between students, teachers and parents become less.
Evaluation of Iran's pharmaceutical policies in the import of drugs and determining the nature of imported drugs using the ABC-VED Method

Background: The supply of medicines in every country is vital in any country, and access to appropriate medicines ensures the health of that community by preventingthe spread of smuggling. The present study aimed to evaluate the current policies of Iran to supply medicines through importation and examine the application of the ABC-VED (Always, Better, Control-Vital, Essential, Desirable) method in assisting policymakers in making decisions on the medicine importation.&#x0D; Method: The present research study was conducted in qualitative and quantitative phases. In the qualitative phase, face-to-face interviews were conducted with 13 health experts in the field of production and import of medicine and their "content analysis" was done using MaxQDA 18 software.In the quantitative phase, to determine the nature of imported drug items, the ABC-VED analysis matrix and the information available in the pharmaceutical statistics of 2019 were used. Then, the distribution of drugs in each of the matrix categories was determined.&#x0D; Result: In the qualitative phase of the study, experts pointed to the impact of restrictive policies on importation of medicines, reducing access to medicines, increasing smuggling, reducing innovation, weakening marketing, and reducing the quality and increasing price of domestically produced medicines. In the quantitative phase, it was found that AV category consists of 36, AE 145, AD 85, BV 31, BE 240, CV 126, CE 970, and CD 672 type of medicines using the ABC-VED matrix. Finally, 21.5 % of medicines were categorized in group I belonging to vital and expensive medicines, 7.2 % in group II that are essential medicnies with moderate prices, and finaly 1 % were categorized in group III which are desirable medicines with lower prices.&#x0D; Conclusion: According to the opinions of experts in the country pharmaceutical industry, Iran's policy on drug importations has always been contractionary. Although it has led to lower prices and increased patients' access to medicines, it made side effects on the pharmaceutical system. Thses side effects includ sectional medical shortages over time. Policymakers can restrict the import of expensive and small quantities of drugs and allocate more funds to the supply of vital drugs. The analyses used cannot be the criterion for decision alone and can only indicate drug priorities in budget shortages and must make decisions within a multi-criteria decision framework.
A Conspectus Study on the Blockchain Technology in Indian Banking Sector

The study is intended to analyze the utilization of blockchain innovation or blockchain technology (BCT) in the Indian banking sector and its advantages in financial tasks. It also covers the field examination concerning how existing BCT is pushing banks to adequately and productively screen and control the financial cycle. The final results show that COVID -19 has given a push to digitization in the sector. The sample data for the study are the 4 Commercialized banks and a number of FinTech organizations in India. Google Trend and Statista method are adopted for the study of perception of consumers. The key advantages of BCT application identified are decentralization, trust, and security in exchanges.
Binary Cyclotomic Polynomials: Representation via Words and Algorithms

Cyclotomic polynomials are basic objects in Number Theory. Their properties depend on the number of distinct primes that intervene in the factorization of their order, and the binary case is thus the first nontrivial case. This paper sees the vector of coefficients of the polynomial as a word on a ternary alphabet \(\{-1,0,+1\}\). It designs an efficient algorithm that computes a compact representation of this word. This algorithm is of linear time with respect to the size of the output, and, thus, optimal. This approach allows to recover known properties of coefficients of binary cyclotomic polynomials, and extends to the case of polynomials associated with numerical semi-groups of dimension 2.
Performance Analysis of Clustering Algorithms for Dyslexia Detection

Clustering algorithms plays a vital role in analyzing and evaluating vast number of high dimensional health care data ranging from medical data repositories, clinical data, electronic health records, body sensor networks, IoT devices, and so on. Dyslexia, a learning disorder, is a common problem that is found in children during the initial stages of formal education, which is detected as mild to severe. It can also be one of the reasons of failure in the school. According to the literature, this difficulty is commonly seen among special needs children in education. There are few studies focused on the application of classification algorithms for detecting the presence of dyslexia. This paper focuses one of the SDG goals, Goal 4: Quality Education, as dyslexic students can be given equal and quality education. Analyses of an online gamified test-based dataset is done by applying various clustering techniques, such as K-Means, Fuzzy C-Means, and Bat K-Means to assess their effectiveness in detecting the problem dyslexia. As the dataset is large, it is observed that usage of clustering methods gives us gain insight into the distribution of data to observe characteristics of each cluster. The clustering results are evaluated using root mean squared error (RMSE), mean absolute error (MAE), Xie-Beni index, and it is found K-Means outperforms FCM and Bat K-Means algorithm for analyzing different levels of the learning disorder.
Development of Automated Tajweed Checking System for Children in Learning Quran

Quran is learned at the early stage of Muslim children and usually taught by the religious teachers. It must be recited with precise and correct tajweed in order to avoid the misunderstanding of its meaning. Sometimes the children recite Quran without the presence of the teacher which the children tend to recite Quran wrongly since there is no guidance. Besides, different children have different learning style since some are visual learners and others are audio learners. In order to help the children to learn Quran in an attractive way, an Automated Tajweed Checking System for Children in Learning Quran is proposed. This system not intended to replace the role of the teachers but to attract the children in learning Quran and help the children to learn Quran without the presence of the teachers. The method of the project uses the concept of voice recognition. In voice recognition there are a few steps involve which are pre-processing, feature extraction, feature classification and recognition. The feature extraction technique used is Mel-Frequency Cepstral Coefficient (MFCC) while for feature classification and recognition technique used is Hidden Markov Model (HMM). This proposed system is believed to recognize recitation efficiently, thus helping children in learning Quran once completed.
Social Canges in Romanticism Period in Jane Austen’s Novel Pride and Prejudice

The purpose of this study (1) to determine the social changes that occurred in the romanticism period by Mr. Darcy and Elizabeth Bennet. (2) and to find out how social changes can cause someone to opposing the social status in that occurs in the novel Pride and Prejudice. In this case the research method used is descriptive qualitative method. To identify and analyze data. The data sources of this study were novel, journals and web articles related to social changes It can be concluded that social change occurred during the romanticism period as created in the novel Pride and Prejudice. That writer hope this research can benefit all students who learn novel and become a learning resource.
Who is we? Disambiguating the referents of first person plural pronouns in parliamentary debates

This paper investigates the use of first person plural pronouns as a rhetorical device in political speeches. We present an annotation schema for disambiguating pronoun references and use our schema to create an annotated corpus of debates from the German Bundestag. We then use our corpus to learn to automatically resolve pronoun referents in parliamentary debates. We explore the use of data augmentation with weak supervision to further expand our corpus and report preliminary results.
Graph-based Retrieval for Claim Verification over Cross-document Evidence

Verifying the veracity of claims requires reasoning over a large knowledge base, often in the form of corpora of trustworthy sources. A common approach consists in retrieving short portions of relevant text from the reference documents and giving them as input to a natural language inference module that determines whether the claim can be inferred or contradicted from them. This approach, however, struggles when multiple pieces of evidence need to be collected and combined from different documents, since the single documents are often barely related to the target claim and hence they are left out by the retrieval module. We conjecture that a graph-based approach can be beneficial to identify fragmented evidence. We tested this hypothesis by building, over the whole corpus, a large graph that interconnects text portions by means of mentioned entities and exploiting such a graph for identifying candidate sets of evidence from multiple sources. Our experiments show that leveraging on a graph structure is beneficial in identifying a reasonably small portion of passages related to a claim.
A New Strategy To Get Students’ Reading Back On Track

The Long Eaton School have been successfully utilising Accelerated Reader and Star Reading since 2013. In August 2020, new Qualified Teacher Librarian ...
GridTrack: Detection and Tracking of Multiple Objects in Dynamic Occupancy Grids

Multiple Object Tracking is an important task for autonomous vehicles. However, it gets difficult to track objects when it is hard to detect them due to occlusion or distance to the sensors. We propose a method, “GridTrack”, to overcome this difficulty. We fuse a dynamic occupancy grid map (DOGMa) with an object detector. DOGMa is obtained by applying a Bayesian filter on raw sensor data. This improves the tracking of the partially observed/unobserved objects with the help of the Bayesian filter on raw data, which has a powerful prediction capability. We develop a network to track the objects on the grid and fuse information from previous detections in this network. The experiments show that the multi-object tracking accuracy is high with the usage of the proposed method.
The Construction of a Valid and Reliable Instrument to Measure Virtual Learning Environment Success

The Virtual Learning Environment (VLE) technology has become an essential element to support 21st-century teaching and learning approaches. To ensure that this technology can be employed effectively by the teachers, the assessment of VLE success is necessary. However, few measures of VLE success amongst teachers exist. Therefore, this article describes the process of the development and validation of a questionnaire to measure the VLE success from the teacher’s point of view. The construction of this questionnaire has been done through a series of procedures, starting by generating the items, conducting face validation and content validation, translating, as well as piloting the questionnaire to a number of selected respondents. As a result, 45 robust items to evaluate VLE success among teachers have been yielded.
Improving Reading Comprehension Skill through the School Literacy Movement for Children with Learning Difficulties

One of the obstacles faced by children with learning difficulties is the low level of reading comprehension. This problem was found in elementary school, Indonesia, children who have learning difficulties have a low level of understanding. The purpose of this study was to determine the effect of the school literacy movement in improving the reading comprehension skills of children with learning difficulties. The method in this study using quantitative research. From the results, there are still some students who do not know the school literacy movement. Students' understanding of the literacy movement towards reading texts can be improved by providing interesting and illustrated reading texts online using the Zoom Meeting application with educators. The results of the research showed that the post-test value was 61.9% greater than the pre-test value of 47.6%, so the difference was 14.3%. Therefore, we can improve students' reading comprehension skills in school literacy activities.
LibGuides: Work-Study: Work-Study Orientation

Complete the Orientation PowerPoint and submit the application below - then complete the survey on the next tab.
Software Risk Assessment and Management with Rules Based on Fuzzy Approach

Up to now, several software risk parameters have been determined in order to assess and manage software development projects: Productivity, Engagement, Attention to Quality, Code Based Knowledge and Management, Adherence to Coding Guidelines and Techniques, Learning and Skills, Personal Responsibility and etc.However, there isn't any universally accepted methodology to apply software risk assessment and management.There are three main reasons of this situation: Firstly, each part of software creation is unique.There is no compelling reason to assemble two times the same parts of software as it might be duplicated by copying it.This makes it truly difficult to make a formal and thorough correlation between two parts of software.Secondly, the current technology is something that changes at a truly fast phase.So, each time a methodology in respect to a certain wave of technology is dependable enough, it is for the most part as of recently old.Thirdly, there is a gigantic zone for innovativeness in discovering the diverse answers for a unique issue.Because of these reasons, the technique "Fuzzy Approach" has a very convenient and proper process for defining software risks due to their nature that has no certainty -uncertainty -structure and principle.Also, software risks are defined as the probability and the severity of damages that are caused by occurring of bad or undesirable events in a system.Thus, the system suffers from strategic, financial, operational, structural or integrity loss and damage.So, there is need to apply and carry out an efficient "Software Risk Assessment and Management" in order to determine and recognize software risks on time before causing problems and troubles into software projects for providing successfully accomplishment in software development process.In this paper, usability and efficiency of "Fuzzy Approached" linguistic and logical rules based on "Fuzzy Logic" in "Software Risk Assessment and Management" have been shown and expressed in detail.
Purple Team Security Assessment of Firmware Vulnerabilities

The purple team concept in offensive and defensive security is related to a set of methods, processes or activities that will combine red and blue team to cooperate in order to create a solid security operations team for improving due-care and due-diligence policies in a company or institution. The accelerated evolution of communication technologies that reached also industrial areas, as well as the complexity rising of new security threats have led to the need of security assessment at component and system level. In this paper we present the purple team methodology illustrated by a firmware security analysis of a communication component form the red team perspective, presenting also an analysis report of the threat related information that we were able to collect. We conclude by proposing recommendations for mitigating attacks from the blue team perspective and presenting the integrative approach of the purple team.
Students’ Perception on the Influence of Marijuana Smoking on Social Behaviour and Academic Performance in Federal University Lafia

Students’ involvement in drug use and drug abuse has increased with very negative consequence. This study investigated the influence Marijuana has on students’ social behaviour and academic performance in Federal University Lafia. Questionnaires were administered on a sample of 190 students. The study utilized both primary and secondary data. Probability method of sampling was employed applying simple random sampling as well as systematic random sampling technique. Survey research methods were adopted and instruments used for data collection were triangulation of questionnaire and in –depth interview. The statistical tool used was frequencies from descriptive statistics. The findings revealed that reasons accountable for marijuana intake include peer pressure, lack of parental guidance, emotional stress, and poor performance in exam, loss of memory and sleeping during lectures, late coming. The study recommends that sensitization of the students on the side effects of marijuana smoking by presenting evidence based on health effects, student education programmes and the resocialization of students by the significant others would go a long way in reducing the menace of marijuana smoking in Federal University Lafia (FULafia).