Reviewerly/exHarmony huggingface dataset:
Graph neural networks for classification: models and applications

Graph neural networks have emerged in the past years as very promising methods for the analysis of graph-structured data. Useful insights can in fact be extracted by allowing learning models to take into account relationships between entities in a graph. The main methods used in the context of graph neural networks are here described and compared, with a focus on the extension of convolutional layers to graph structures. Afterwards, an analysis of how attention mechanisms integrate with graph neural networks is introduced. In this context a new method is proposed for allowing a graph neural network to attend over its own input in the context of graph classification. An application of these methods to biomedical data is finally presented, with an example in the field of Parkinson's disease classification.
Increasing Authorial Leverage in Generative Narrative Systems

Author(s): Garbe, Jacob | Advisor(s): Mateas, Michael; Wardrip-Fruin, Noah | Abstract: Generative narratives are an important subset of interactive narratives in games, enabling works that can provide unique media experiences not possible through more static forms. Such experiences can include character dialogue-driven games, systemic games with narrative bindings to mechanics, dynamic narratives responding to player actions, and many other forms. However, the concomitant authorial burden from creating content for these systems, in comparison with static narrative media, often makes completing generative narrative experiences difficult or infeasible.This dissertation contributes a framework for evaluating and developing generative narrative systems while avoiding runaway authorial burden. This Authorial Leverage Framework was generalized from pragmatics learned through implementing three generative narrative systems in three particular spaces of interactive narrative, which represent three additional research contributions. The Ice-Bound system uses thematic-driven combinatorics to explore the sculptural space of vignette-style stories, seeking to maximize uniqueness while minimizing authorial overhead. StoryAssembler is a hybrid forward state space planner and hierarchical task network (HTN) planner, created to explore how choice-based narratives could be dynamically generated from diegetically embedded planner parameters. Lastly, the Delve system seeks to create vignettes whose text can be manipulated and sculpted through an ontologically-connected 3D object system. Each of these systems presented their own particular challenges, which were confronted head-on with the intent of creating fully realized interactive experiences. In the course of doing so, pragmatic lessons were learned, which were generalized to form The Authorial Leverage Framework.It is my hope that this framework and these systems will provide a useful tool for other practitioners and scholars in this area, grounded as they are in the production of playable experiences, whose creation is a critical component of systems-driven scholarship.
Metadata Validation Using a Convolutional Neural Network : Detection and Prediction of Fashion Products

In the e-commerce industry, importing data from third party clothing brands require validation of this data. If the validation step of this data is done manually, it is a tedious and time-consuming ...
Progress Report on the Scala Algebra System

The new extension methods in Dotty (codename for Scala 3) allow us to solve a long-standing problem with type classes and coercion. It enables the realization of a new Scala adapter for the Java Algebra System (JAS). Our design is compared to the existing Scala DSL for the Rings computer algebra library, and shown to be interchangeable with it. The question whether Scala can be used for library development is raised, and it turns out to be adequately efficient, taking advantage of the new language inline feature for code specialization.
An Improvement of Line Segment Detection Algorithm Based on Convolutional Neural Network

In order to improve the accuracy and integrity of line segment detection, this paper presents an improved algorithm for line segment detection based on convolutional neural network. First, we use a full convolutional neural network to extract endpoints information from the image, the endpoint information includes the position of the endpoints and the direction of the line connected to the endpoints. Then, we use the stacked hourglass network to generate a line heat map of the image, the larger the value of each pixel in the line heat map, the more likely there is a line. Finally, in order to reduce false detection, a method of generating a straight line combining the endpoint information and the line heat map is proposed. Experimental results show that the algorithm effectively reduce line segment detection errors and improve integrity of line segment detection, and it can be applied to tasks such as 3D reconstruction and scene understanding.
The Role and Strategy to Stimulate Language Development in Early Childhood During Covid-19

Abstract: The development of aspects of language in human life is very important. A language is a tool of education and interaction between individuals. Language development problems in early childhood that often arise are late language emergence (LLE). From some previous studies, stimulation and education factors become guidelines for teachers and parents in providing appropriate stimulation through the principle of play while learning and adapted to the development and age of the child. The purpose of this study is to describe the role and strategy of stimulating children's language development during the COVID pandemic. The design of this study uses the method of literature study or literature review. The results and discussion of strategies for developing children's language for 1-2 years old can be done by 1) Mothering, 2) Recasting, 3) Echoing 4) Expanding 5) Labeling. While strategies for developing children's language for ages 3-6 years 1) Increasing Interaction and Communication with Children 2) Reading aloud, 3) Involving Children in Storytelling, 4) Providing literacy activities. Keywords: strategy, language development, early childhood, covid-19.
Effects of Corruption on Tertiary School Enrolment in Africa

This paper empirically analyses the effects of control of corruption on tertiary school enrolment in a panel of 44 African countries over the period 1996-2016.Using system Generalized method of moments and controlling for a large number of other determinants of tertiary school enrolment, it finds that, over the sample period, control of corruption has a substantial positive effect.This is probably because control of corruption increases public spending level and effectiveness on tertiary education, increases the return on tertiary education, and ultimately fosters the access to tertiary education specially the poorer strata in the African economies.In the light of this result, an intensification of control of corruption in Africa is imperative to improve the tertiary school enrolment.
Research on the Teaching Reform of Equipment Guarantee in Special Environment

Abstract The special topic of equipment guarantee under special environment is one of the special topics in a certain course of a major in the college. Combined with the characteristics of the project, the problems in the teaching of the project are analyzed. In view of the existing problems such as the thin teaching content, the limited teaching resources and the single teaching methods, this paper puts forward the specific teaching reform measures for the special equipment guarantee topic in the special environment from four aspects: reconstructing the teaching content system, improving the teaching methods, enriching the teaching resources and improving the teachers’ teaching ability.
LibGuides: Career Exploration: More Help

Resources online and in the library for career exploration, planning, goal setting, accomplishment Get more help when you need it
IMPACT OF ANTI-FORENSICS TECHNIQUES ON DIGITAL FORENSICS INVESTIGATION

Computer crimes have become very complex in terms of investigation and prosecution. This is mainly because forensic investigations are based on artifacts left oncomputers and other digital devices. ...
Securing Azure SQL

Now that you have deployed and configured your Azure SQL Managed Instance or Database, you will want to ensure you have done all the right things to fully secure your Azure SQL deployment. Azure SQL has all the capabilities that come with SQL Server for security plus more.
Desain Arsitektur Aplikasi Penilaian Sikap Siswa Menggunakan standar Experience Application Programming Interface (xAPI)

Nowdays, most of school both public and private has made aspects of student attitudes and skills to be one of the assessment parameters in the report. The teacher evaluates attitude activities by assigning students / parents to record activities in the form of scientific writing, photos and video. The student/parent should reports the activity into a report book of activities by attaching photos, description of time, place and description of activities. However, this raises many obstacles especially in terms of evaluation of learning activities. First, the evaluation process took time longer because it is done manually. Second, the limitations of paper make the documentation of student activities not comprehensive and not realtime. It becomes an opportunity for developing apps to record and analyze all activities. Rapiku (Rapor Afektif dan Psikomotorik Ku) is an mobile app to help teachers and parents monitor and evaluate students activity in a realtime, continuously and accurately. The architecture is designed using Experience Application Programming Interface (xAPI) technology. The App records student activities in the form of photos, videos, hashtags, time and activity descriptions in the form of statements. The statements will be stored in the LRS (Learning Record Store) as the main part of xAPI. The data in the form of statements in the LRS will be processed and analyzed under the learning analytic system. With the standard of xAPI, teacher, school and other educational organizations can aggregate, visualize and analyze educational data mining comprehensively and accurately.
Den digitala vävstugan : En studie av vävning och sociala medier

This essay examines what functions a forum on social media can have for people interested in weaving, and studies what similarities and differences exist between a digital forum for weavers and a p ...
LibGuides: VIRTUAL KMS LIBRARY: Home

A guide to all things library related and beyond at John F. Kennedy Middle School, Natick, Ma.
AN ERROR ANALYSIS ON THE USE OF PAST TENSE IN THE STUDENTS WRITING ON RECOUNT TEXTS (A Descriptive Qualitative Study at the Eighth Grade Students of SMP N 1 Tengaran)

Khabibawati, Afi. 2020. “An Error Analysis On The Use Of Past Tense In The Students Writing On Recount Texts (A Descriptive Qualitative Study At The Eight Grade Students of Smp N 1 Tengaran)”. A Graduating Paper. English Department State Institute For Islamic Studies (IAIN) Salatiga. Counselor: Sari Famularsih, S.Pd., M.A.This research is about error analysis on the use of simple past tense in English recount text made by the students of SMP N 1 Tengaran in the academic year of 2019/2020. The objectives of this research were to find out types of errors that occurs on the use of simple past tense in English recount text written by the eighth grade students of SMP N 1 Tengaran in the academic year of 2019/2020 and to find out the dominant errors on the use of simple past tense in English recount text written by the eighth grade students of SMP N 1 Tengaran in the academic year of 2019/2020. The methodology of research was qualitative research especially descriptive study. The techniques of collecting data was written test to find out the types of errors that occurs on the use of simple past tense in English recount text written by the eighth grade students of SMP N 1 Tengaran, and to find out the dominant errors on the use of simple past tense in English recount text written by the eighth grade students of SMP N 1 Tengaran. The result of this research showed that there are four types of errors that occur; they are error of omission (28,57% or 18 errors), error of addition (12,69% or 8 errors), error of misordering (6,34 or 4 errors) and error of misformation (52,38% or 33 errors). From the data analysis the researcher found that the most dominant error students made is error of misformation. Error of misformation relates to the use of the wrong form of the morpheme or structure.
DATABASE MANAGEMENT FOR FACIAL RECOGNITION SYSTEM

The face is one of the easiest ways to differentiate the individual identity of each other. Face recognition is a personal identification system that uses personal characteristics or facial features of a person to identify the person's identity. The most used human face recognition process is face detection ,where this procedure takes place very quickly in humans, except under certain conditions where the object is located at close distance. The purpose of this project is to develop face recognition based automated student attendance system. In order to achieve high quality performance, the test images and training images of this proposed approach are limited to frontal and upright facial images that consist of a single face only. The test images and training images have to be captured by using the same device to ensure no quality difference. In addition, the students have to register in the database to be recognized. The enrolment can be done on the spot through the user-friendly interface.
A Model for Evaluating the Effectiveness of an Undergraduate Curriculum in Teaching Software Code Quality

Developers build an entire software by writing quality code, the failure of which can risk organizational reputation, financial wellbeing, and even the lives and security of people. The ability to ...
Att utläsa räknestrategier från ögonrörelser

This study aims to investigate the information that can be collected about countingstrategies when tracking a person’s eye-movements when he/she is doing a mentalcalculation on a given expression. ...
SDCC Library: Linking to Library Resources in Canvas: EBSCO Article & e-Book Databases

How to link to SDCC Library resources within a Canvas course shell Finding persistent links in EBSCO article databases like Academic Search Complete, Business Source Premier, CINAHL, and the EBSCO e-Book collection.
UNIRI - Thermal image dataset - UNIRI-TID

The dataset contains thermal images extracted from videos that simulate illegal movements around the border and in protected areas. Videos are recorded at night in clear weather, rain, and in the fog, at different ranges, and with different movement types – running, walking, and sneaking. From all recordings, about 20 minutes of material from the clear weather scenario, 13 minutes from the fog scenario, and about 15 minutes from rainy weather were selected for further processing and frames extracted from the video. Of all the frames, 6,111 were selected to include different weather conditions and were manually annotated. Due to different weather conditions, the set contained 2663 frames taken in clear weather conditions, 1,135 frames of fog and 2,313 rain frames.
Context-Aware Based Discriminative Siamese Neural Network for Face Verification

Although face recognition and verification algorithms have made great success under controlled conditions in recent years. In real-world uncontrolled application scenarios, there is a fundamental challenge that how to guarantee the discriminative ability of feature from vary inputs for face verification task. Aiming at this problem, we proposed a context-aware based discriminative siamese neural network for face verification. In fact, the structure of facial image are more stable rather than hairstyle change and wearing jewelry. Firstly we use a context-aware module to anchor facial structure information by filtering out irrelevant information. For improved discrimination, we develop a siamese network including two symmetrical branch subnetworks to learn discriminative feature by labeled triad training data. The experimental results on LFW face dataset outperform some state-of-the-art face verification methods.
Enhanced SMOTE & Fast Random Forest Techniques for Credit Card Fraud Detection

The credit card payment industry has steadily grown over the last decade with ascend and extensive use of the internet. Credit card is a means of payment without getting cash in hand for purchasing or selling products or services. It is an easy way of automatically providing credit to a customer. Fraud in the credit card industry has turned out to be a big issue. Credit card fraud results in damages of billions of dollars for online traders, credit card users & it is a serious concern of great significance.Identification of financial crime and risk management are important for banks and business organisations. The predictive models for the detection of credit card fraud are in active use in practise, there are relatively few documented studies on the use of data mining approaches for the detection of credit card fraud, likely due to lack of study data available and reluctance to share it for a potential intangible loss.The proposed approach suggests a smart credit card fraud detection model which can detect fraud from extremely imbalanced and unspecified credit card transaction dataset. The proposed fraud detection model is based on 3 phases, including pre-processing in which redundant attributes are eliminated, and also ranks characteristics using the Fast Random Forest model by their significance. After pre-processing, the issue of class imbalance is addressed by the Enhanced SMOTE (Synthetic Minority Oversampling Technique) technique, and the final step is to classify whether Fast Random Forest performs a new transaction is either fraudulent or legitimate. In this research work, we have used UCSD FICO (University of California San Diego Fair Isaac Corporation) data mining competition dataset for performance assessment of presented approach.
Bayesian Mixture Models for Latent Class Analysis

Bayesian mixture models provide rich and flexible class tools which are particularly useful when there is unobserved heterogeneity in the data. When the number of subpopulations, called components, is assumed random, we allow the data to determine the complexity of the model. The latter property allows us to include a finite mixture model with a random number of components into the wider class of Bayesian nonparametric models. In this paper we consider multivariate discrete data, so that the class of mixtures is also referred to as latent class models. In particular, we let the number of latent classes to be random, and resort to Bayesian nonparametric techniques to devise a MCMC algorithm. The model is illustrated on an benchmark application dealing with role conflict.
Applying Design By Contract to Remote Procedure Call Interface Definition Languages

Design by contract, abbreviated as DBC, is a software development methodology that aims to increase the reliability and robustness of software components. While a fair amount of research has been d ...
An Empirical Study on the Core Literacy of College Students' Physical Education and Its Influencing Factors

The cultivation of the core literacy of Tibetan college students' physical education is the direction and goal of the reform of public physical education in Tibetan colleges and universities. It is an important measure to implement the concept of Enhance morality and Foster talents and the idea of Health first. It is helpful to the formation of Tibetan college students' sports health literacy and promote the all-round development of Tibetan college students. Using the method of random stratified cluster sampling, a questionnaire survey was conducted on the core literacy and its influencing factors of 1474 Tibetan college students in 4 undergraduate colleges in Tibet Autonomous Region. The study found that the overall core literacy of Tibetan college students in physical education is better, but the development of the three parts of athletic ability, healthy behavior and sports morality are slightly uneven. School-level factors and personal-level factors are highly related to the formation of the core literacy of Tibetan college students' physical education disciplines, and family-level factors and social-level factors are moderately related.  Recommendation: To give full play to the main position of school education and comprehensively improve the core literacy level of Tibetan college students in physical education. Based on the penetration of social education, create a good atmosphere for Tibetan college students to participate in physical exercise. Pay attention to the orientation of family education and stimulate the interest of Tibetan college students to participate in physical exercise.
The Effectiveness of Psychodrama in the Treatment of Anxiety for Students of Art Education Department

Anxiety is an emotion that results of the learner’s fear of future and what threaten his being and his life continuation and stability, which made him feel dejected, nervous and psychologically unstable. Therefore, it is necessary to control these fears and threats by the use of psychodrama as a means for the learner to comprehend the world in which he lives through awareness and experiment that help them to cope and assimilate in the society to get rid of anxiety. It appeared to the researcher through a survey study that there is anxiety that overcomes them due to fear of future in case of failing to comprehend the new life tasks. That encouraged him to think of using practical and scientific mechanism to get rid of that anxiety by using the psychodrama to treat some of the psychological cases foremost of which is anxiety. The study is structured in four chapters: Chapter One includes the methodological framework, that is, the problem, importance, objective and hypothesis of the study. The present study aim at examining “the effectiveness of psychodrama in the treatment of anxiety for students of art education department”.  To verify the above objective the following zero hypothesis was formulated (there is statistically significant difference at the level of 0.05 between the average score of students of experimental group and control group in the Skill Performance Test) as well as the limit and term definition. Chapter Two is consecrated to the theoretical framework which is sibdivded into two inquiries: the first inq. deals of psychodrama (concept, busies, elements), while the second inq. deals with anxiety (symptoms, types and reasons). Chapter Three deals with the methodology and procedures of study in terms of research community, sample and the experimental design adopted by the researcher for the skill test. Chapter four includes result displat and explanation as well as conclusion and recommendations.
Keystroke dynamics for student authentication in online examinations

Biometrics are distinctive for each person, and can not be given away or hacked like a password. Keystroke dynamics is a behavioral biometric characteristic that can be used as a complementary auth ...