Reviewerly/exHarmony huggingface dataset:
One Semicolon Away from Success: Rebranding "failure" in CS1 through New Terminology

In a review of student programming work (through playback of their submissions via online IDE), it was noted that students could be quite close to a successful solution and repeatedly start over, deleting all of the work done to that point in time. The words of Thomas Edison expressed the problem associated with this current branding: "I have not failed. I've just found 10,000 ways that won't work." While this is meant to imply that failure has led towards success, the idea that something "won't work" captures the mindset that students are facing when using the word 'failure' in regards to programming. In fact, iterations of programs move students incrementally closer to their goal. The notion of a binary concept like pass/fail being applied to programming leaves less room for creativity and exploration. Amongst new programming students, after reaching this point of 'passing', student fear of modifying and 'playing' with working programs has been noted. In order to address the concerns of students and help shift student mindsets away from 'failure' towards 'incremental improvement', a rebranding exercise must take place.
INFLUENCE OF WHATSAPP ON ACADEMIC PERFORMANCE OF UNDERGRADUATES IN KWARA STATE

WhatsApp is a smartphone application for instant messaging. It is an amazing application, which has helped students and teachers to connect to the society and the world at large. The question many people
Exploring the inter-grade dividing criteria of the elementary grade group English textbooks: Sequence analysis of the communicative functions of listening dialogues

The purpose of this study is to explore inter-grade dividing criteria of the 2015 grade group elementary English textbooks. Elementary English textbooks consist of two grade groups: the 3rd and 4th grade group and the 5th and 6th grade group. L2 Syntactic Complexity Analyzer(L2SCA) is utilized to investigate the dividing criteria of the communicative functions implemented in these textbooks. Subjects of the analysis were the listening dialogues for their structural sequencing of 3rd to 4th graders and 5th to 6th graders separately within their own grade groups. Data were processed and analyzed using SPSS 25.0 and independent sample t tests for inter-grade textbooks for 14 L2SCA statistical indices. The findings are: 6 indices out of the 14 L2SCA statistical indices turn out to be critical for dividing the 2015 grade group elementary English textbooks. The 6 indices are mean clause length, mean sentence length, mean t-unit length, mean complex noun phrasal number per phrase and per t-unit and mean number of verb phrases per t-unit. Based on the findings, it is suggested that a standardized criteria derived from these 6 indices can be provided as an inter-grade dividing criteria of the 2015 grade group elementary English textbooks.
Computational Methods for Next-Generation Online Media Ecosystems

Author(s): ElSherif, May | Advisor(s): Belding, Elizabeth | Abstract: Human biases have found their way into our digital footprints. Human corpora and human forms of expression mirror biases inherent in societies explicitly or implicitly.Now, information all around us is tainted with these biases. This has led to severe consequences from a technological perspective. First, social and cultural biases have found their way into technology, and in particular into automated tools that rely on human-generated data leading to discriminatory systems [1]. Secondly, while online information ecosystems provide freedom of expression and give voice to individuals, they have also suffered a wave of disorder due to the prevalence of malevolent online misuse, manifested as hate speech and online misinformation, such as fake news. These problems are motivated by bias and present unprecedented challenges because they cannot be solved in a traditional linear fashion, since the problem definition evolves as new possible solutions are considered and/or implemented [2]. In this thesis, we investigate the digital representations of these prejudices including issuesof gender equality and hate speech.In the first part of the thesis, we begin by analyzing stories of women sharing their harassment experiences and show how targets of gender-based violence utilize social media to shift their cognitive states by leveraging storytelling. We then move into studying gender bias representations in Natural Language Processing. We provide a comprehensive review of current methods that attempt to debias corpora and prevent bias amplification in machine learning models. We then show that current Neural Relation Extraction systems exhibit gender bias.In the next part of the thesis, we focus on online hate speech and its nuances on social media. In order to design automated hate speech detection systems, we must empirically study existing instances of hate speech. We present the first set of online hate speech studies that investigate hate instigators and hate targets, linguistic properties of directed and generalized hate speech, and online hate communities. As a result of this work, we make publicly available a high precision dataset of 28K tweets, currently the largest Twitter hate speech dataset available to the research community. Our work includes a one of a kind set of analyses pertaining to hate speech that have impacted the design of hate speech detection systems by improving the F-1 score of hate speech detection and classification systems in online social media by an average of 10%.Our work enables the design of the next-generation hate speech detection systems and gender bias detection and mitigation systems. We conclude with an overview of our key findings as well as a discussion of future research directions inspired by the work in this dissertation.
Development of color correction system for medical images using color charts

For image devices such as cameras and displays, it is difficult to obtain consistent color reproducibility due to individual manufacturer designs. We propose to improve the color reproducibility of medical images by using color charts. With the spread of COVID-19 infection, the need for telemedicine is increasing from the perspective of infection prevention. In addition, the digitization of medical images will progress in the future, and it is required that the color reproducibility of supervised data at the time of image acquisition be improved for learning / diagnosis assistance by AI. Colors in the specialized field of medical image processing are largely processed in non-standardized methods, raising many challenges in use cases where color is used for diagnostics. Smartphones are used in telemedicine, but color reproducibility may decrease due to differences in lighting as well as equipment, which may lead to a decrease in diagnostic accuracy. We have developed color charts and appropriate image processing algorithms for medical use cases. In the AI accuracy verification in pathological diagnosis, it was also confirmed that the AI diagnosis accuracy can be improved by performing image processing using a color chart.
Penerapan Metode Euclidean Probality dan Confusion Matrix dalam Diagnosa Penyakit Koi

Koi fish aquaculture is still susceptible to fish’s diseases. The farmers’ limited knowledge about koi fish diseases, especially the novice farmers, to overcome this problem which has impact on the koi fish harvest to be decreased, and even tends to losses for the farmers. The creation of an AI system for diagnosing koi fish diseases using “the euclidean probability and confusion matrix” method is needed as a solutions for farmers to discover the solutions if their fish are get diseased. AI system with “euclidean probability and confusion matrix” methods created using 10 diseases and 23 symptoms data. Based on that, 10 rules were obtained. Diagnosis of koi fish disease is carried out by entering the symptoms of koi fish disease and calculating the percentage based to the appropriate rules. After the disease was picked based on largest percentage. After obtaining a diagnosis of the disease, testing using confusion matrix is performed. The test results from 93 test data show a precision level of 93.67%, a recall rate of 88.21%, an accuracy level of 95.91%, an error rate of 4.09% and an f-measure level of 85.27%.
TEACHING READING IN HOME LANGUAGE AT FOUNDATION PHASE: AN ANALYSIS OF CONTEXTUAL ISSUES

Ponte Academic JournalFeb 2021, Volume 77, Issue 2 TEACHING READING IN HOME LANGUAGE AT FOUNDATION PHASE: AN ANALYSIS OF CONTEXTUAL ISSUESAuthor(s): Mettse Juliet Masalesa ,Duduzile Nkomo, Buyisani DubeJ. Ponte - Feb 2021 - Volume 77 - Issue 2 doi: 10.21506/j.ponte.2021.2.8 Abstract:This study analysed the contextual issues that are an integral part in the teaching of reading in Sepedi (HL) in Mpumalanga Province. Bronfenbrenner’s social ecological systems theory underpinned this study. An ethnographic case study design that is an interpretive paradigm was used. Four schools (A, B, C & D) were sampled in the study and in each of these; two teachers were purposively selected as participants. Individual interviews, classroom observations and document analysis, were used to collect relevant data. This was analysed thematically. The process involved data organisation, coding and categorising it into different themes as directed by the study. The major findings were that there is lack of clear policies on the teaching of reading in home languages like Sepedi. Furthermore, there is an indisputable shortage of Sepedi reading materials in schools and this affects the development of a reading culture in learners amongst other issues. Poor parental involvement also seemed to be another impediment to anticipated learning outcomes. This article therefore argues that the development of policies, which are specific on the teaching of home languages like Sepedi, should be prioritised. In addition, the government and other relevant stakeholders must continuously thrive to ensure the provision of adequate reading materials in schools. Above all, schools must create leastrestrictive environments that encourage active participation of parents in the entire teaching and learning process. Download full text:Check if you have access through your login credentials or your institution Username Password
Alias Identification from Narratives for Question Answering

Alias is the term used to give a person’s name after giving his or her real name. The name can be Pronouns or Generic (Noun Phrases) NPs. For identifying pronouns co-reference resolution is being used. Identifying Generic NPs from a narrative is a crucial task, because we observed that standard Natural Language Processing (NLP) tool-kits work poorly for generic NPs. NLP applications using the co-reference resolution technique are Timeline creation, Question-answering, Summarization and Information extraction. In this work, we propose an approach using linguistic knowledge for Alias Identification and Question Answering system to answer the given question. For encoding the linguistic knowledge Markov Logic Network (MLN) is used. The proposed system is a combination of Alias Identification and a Question Answering. Public narratives/paragraph of varying linguistic complexity is selected as input to the alias identification system. Input to the question answering system is output alias identification system and question. From the narratives/paragraph answers to the corresponding questions will be extracted. The system generates the answer sentence by finding the first pronoun or generic NP which is replaced with canonical form.
An error analysis method for attitude estimation system based on epipolar geometry

This paper proposes an error analysis method based on epipolar geometry which is analyzed for improving the accuracy of attitude estimation. The influence of equivalent focal length and principal point coordinates on modeling error was analyzed by simulation and experiment based on a rotary table. The result shows that the influence of the equivalent focal length will increase as the rotation angle increases, the different motion states will lead to different degrees of impact of the principal point coordinates. Besides, we derived that pose measuring accuracy is unrelated to the magnitude of rotation angle and there is no accumulative error under simulation conditions. This proposed method can enhance the measuring accuracy and provide some meaningful advice for engineering applications.
Analisis Proses Pembelajaran Menggunakan Aplikasi Google Classroom pada Masa Pandemi Covid-19

Nowdays, Covid-19 pancemic makes all education elementsmust do the adaptation of the situation. Online learning system is the first choiceto be did. The purpose of this research describe the analysis of the learning process of Pendidikan Agama Hindu dan Budi Pekerti online based using the google classroom application in VII grade at SMP N 2 Blahbatuh. This study used descriptive qualitative method. Data collection techniques using interviews and documentation. The subjects of this study were students of class VII in the academic year 2020/2021. The number of students is 100 people. The results showed that the google classroom application can help and facilitate teachers and students in implementing the distance learning process. Based on the results of the study it can be concluded that online learning using the google classroom application proved effective carried out during the WFH consequence covid-19 pandemic. Utilization of Google classroom is acceptable and further developed even though it still requires revamping the availability of supporting resources.
Effective Listing Spam Detection System using Locality Sensitive Hashing at Scale

The popularity, cost-effectiveness and ease of buying and selling that marketplaces like Craigslist, Offerup offer to users has been plagued with the rising number of unsolicited spam listings, fraudulent transactions and in some extreme cases law enforcement also needs to be involved. Driven by the need to protect Offerup users from this growing menace, research in spam, fraud listing filtering/detection systems has been increasingly active in the last decade. However, the adaptive nature of Scammers and Fraudsters has often rendered most of these systems ineffective. While several spam detection models have been reported in literature, the reported performance on an out of sample test data shows the room for more improvement. Presented in this research is an improved spam detection model based on Locality Sensitive Hashing algorithm which to the best of our knowledge has received little attention in spam/fraud detection problems. Experimental results show that the proposed model outperforms earlier approaches across a wide range of evaluation metrics inside Offerup.
Modelling Verbal Morphology in Nen.

Nen verbal morphology is particularly complex; a transitive verb can take up to 1,740 unique forms. The combined effect of having a large combinatoric space and a low-resource setting amplifies the need for NLP tools. Nen morphology utilises distributed exponence - a non-trivial means of mapping form to meaning. In this paper, we attempt to model Nen verbal morphology using state-of-the-art machine learning models for morphological reinflection. We explore and categorise the types of errors these systems generate. Our results show sensitivity to training data composition; different distributions of verb type yield different accuracies (patterning with E-complexity). We also demonstrate the types of patterns that can be inferred from the training data, through the case study of sycretism.
A Design for Recycling: Developing a Mobile Application to Improve Recycling Behavior

Indonesia, as one of the most significant contributors to plastic pollution in the world, pledged to reduce 70 percent of the plastic waste by 2025. However, plastic waste continues to increase and keeps generating through plastic coffee cups from the booming business of coffee franchises in Indonesia. Previous research on factors influencing plastic recycling behaviors and the investigation of the role of mobile apps in the recycling system discusses a prospective mobile app to increase recycling behavior. However, this type of mobile app does not exist in Indonesia yet. Therefore, by employing mixed methods, a mobile plastic waste recycling application is being developed. The results of this study present the following findings: (1) the design process of developing a mobile app for plastic recycling from idealization, sketching, and paper prototyping utilizing features of perceived behavioral intention factors such as personal attitude, perceived behavioral control, and perceived moral obligation; (2) a usability paper prototype resulting in potential for participants to engage and use the app as well as indicate prospective awareness where using the app would likely increase plastic recycling culture. This study has several limitations due to the sample size, the scope of the study, and the content of the app. This study concludes that future work is underway to test the final prototype of the app and the collaboration of the app through a co-design project.
An analysis of Korean high school English textbooks through syntactic complexity and readability

The present study compared the reading passages represented in prescribed English textbooks(High School English 0) and non-prescribed textbooks (High School English 1, 2) used in Korean high schools through lexical complexity and readability. To achieve this purpose, the L2 Syntactic Complexity Analyzer (L2SCA) and three different readability indices, Flesch-Kincaid Grade Level(FKGL), Flesch Reading Ease score (FRE), and Gunning Fog Index (GFI), were utilized. One-way ANOVA and a post-hoc test (Scheffe Test) were performed on 76 passages for High School English 0, and 53 for High School English 1 and 2. Results showed that in terms of syntactic complexity, no statistical differences were found between High School English 0 and 1. On the contrary, High School English 0 and 2 differed across every syntactic complexity measure, and 5 out of 14 measures were significantly different between High School English 1 and 2. With regard to readability, significant differences were observed among the textbooks (i.e., High School English 0/1, 1/2, and 0/2). These results imply more syntactic variation is required between High School English 0 and 1, but that hierarchy is properly being maintained for readability levels across the 2015 revised high school English textbooks.
LibGuides: Open Access : OA Journals

The purpose of this guide to help students at Independent College Dublin understand what Open Access is, how it is changing the way we publish and consume knowledge, and where they might find Open Access resources related to their subject.
Are all Gaussian states also cluster states? Detecting hidden continuous-variable entanglement

Continuous-variable (CV) cluster states are a universal quantum computing platform that has experimentally out-scaled qubit platforms by orders of magnitude. The implementation of CV cluster states uses multimode squeezed Gaussian states and fault tolerance thresholds for CV quantum computing have been predicted for realistic squeezing. An outstanding question has been whether any Gaussian state can be expressed as a cluster state. We show here that Gaussian states can present hidden entanglement, which is not captured by the corresponding cluster state graph and therefore invalidates this graph. Hidden entanglement vanishes in the infinite squeezing limit, which should therefore be used with extreme caution. We derive a general procedure to detect hidden entanglement in an arbitrary Gaussian state and validate it as a CV cluster state. These results are relevant to all experimental implementations of CV cluster states to date.
Study on analysis for reducing sideslip when tire running on rough terrain using SPH method

In recent years, farmer is decreasing in Japan. In addition to this, the number of young people who is important in agriculture has drastically declined because aging is advancing. Along with that, “The smart agriculture” proposed by the Ministry of Agriculture, Forestry and Fisheries, they are trying to improve efficiency by using an automatic control robot. It seems necessary to have a mechanism that this robot does not slide on sloping rough terrain, but it is difficult to verify by experiment. Therefore, we considered to verify by modeling using the SPH method which is one of the meshfree methods.
Fast Short and Fast Linear Cramer-Shoup

A linear Cramer-Shoup encryption scheme version was proposed by Shacham in 2007. Short Cramer-Shoup encryption scheme was designed by Abdalla et al. in 2014. This scheme is a variant of the Cramer-Shoup encryption scheme that has a smaller size. They proved that it is an IND-PCA secure encryption under DDH and the collision-resistance assumptions. We design a faster version of Short Cramer-Shoup encryption scheme denoted Fast Short Cramer-Shoup encryption. We also, proposed a faster version of linear Cramer-Shoup encryption called Fast Linear Cramer-Shoup. We prove that the Fast Short Cramer-Shoup is IND-PCA secure under DDH and the collision-resistance assumptions. We also, show that our linear encryption is CCA secure under the Linear assumption. Finally we run an evaluation of performances of our schemes.
The Effect of Smart Blockchain Contracts on the Financial Services Industry in the Banking Sector in Jordan

The study aimed to identify the effect of smart blockchain contracts on the financial services industry in the banking sector in Jordan, through an empirical study on the Jordanian banking sector. The study population was represented by the banks in the Jordanian environment, (15) banks were selected with their various branches. As for the study sample, it consisted of (81) including (managers, deputy directors, heads of departments, major clients), representing approximately 67.5% of the total sent questionnaires. A questionnaire was used as an instrument of the study in order to collect data from the study population. The descriptive and analytical approach was used. The study concluded that there is a statistically significant relationship regarding the impact of smart blockchain contracts on the financial services industry in the banking sector in Jordan. It was found also that the smart blockchain contracts help to reduce the cost of Banking services and enhancing operational efficiency in Jordanian banks. Moreover, they enhance and develop banking services and upgrade them in Jordanian banks. In light of the results of the field study, the researcher recommended that Jordanian banks should rely on smart Blockchain contracts in the field of banking sector that will contribute to reducing costs related to remittances and raising the operational efficiency of these banks.