Reviewerly/exHarmony huggingface dataset:
USING LANGUAGE CASUAL STYLE IN TEENAGERS 17 YEARSOLD ON INSTAGRAM COMMENT

This research paper aims to find out of casual style used by teenagers of social media instagram. Instagram comment is always used by teenagers to interact with their friends using casual style. This research used qualitative descriptive method. The object of this research is the casual style used on instagram comment by teenagers. The data are casual style words on instagram comment by teenagers used when interact with their friends. The data source is the post on their account on instagram and the researchers taken 9 post from 3 accounts that used on instagram comment and containing casual style that they were used. In analyzing the data, the researchers classifies the data into types of casual styles based on eggins theory.Based on analysis the researchers found that from 3 account and 9 post from their post the researchers conclude that there are 51 casual style that used on instagram comment by teenagers and there are 32 declarative types of casual style , there are 3 exclamative types of casual style, there is 7 introgative types of casual style and the last there are 11 harsh words type of casual style. The total of casual style that used on instagram comment by teenagers are 51 and there are 4 types of casual styles in that instagram comment. This means that the more appear of casual style are in declaratives.Keywords : Casual style, teenagers, instagram commen
Granular Multimodal Attention Networks for Visual Dialog

Vision and language tasks have benefited from attention. There have been a number of different attention models proposed. However, the scale at which attention needs to be applied has not been well examined. Particularly, in this work, we propose a new method Granular Multi-modal Attention, where we aim to particularly address the question of the right granularity at which one needs to attend while solving the Visual Dialog task. The proposed method shows improvement in both image and text attention networks. We then propose a granular Multi-modal Attention network that jointly attends on the image and text granules and shows the best performance. With this work, we observe that obtaining granular attention and doing exhaustive Multi-modal Attention appears to be the best way to attend while solving visual dialog.
The Problems Faced in Learning English for Nursing of Students in STIKes Pemkab Jombang

Introduction: Facing the globalization era, every human have to be able to speak English to make easier the communication in community. In nursing, English become the important in order to every nurse able to compete in globalization era and give the optimal to avoid the misunderstanding of communication. Objective of this study is to analyze the problem of teaching and learning Englishfor nursing that faced in STIKes Pemkab Jombang. So, the problems of students in learning English of four skills, they are speaking, reading, writing, and speaking can be solved to encourage the student’s interest to work in foreign country.&#x0D; Methods: this study used qualitative,it was analyzed,in descriptive analysis.The problems were gained from the casewhichis happened in the classroom. The populations were 62 students in third semester, while the sample size 12 students to ﬁnd the solution in learning English well. 12 students were taken by random sampling from each class in nursing bachelor program as many as 2 students each class. This study used comparative method which was used in a study to narrate the difference of variable of research, this study used as natural condition with collecting the data.Then,itwasanalyzedstatisticallytoﬁndthedifferent of variable. The instruments in this study were observation sheet, questionnaire, and speaking test.&#x0D; Conclusion: The speaking score was constantly improved and the problem of learning English for nursing is solved. On the other hand, from the result percentage of questionnaire, they complete the problem of medical English.
A convolutional neural network with sign-to-position format conversion

This paper tries improving image recognition accuracy with Convolutional Neural Networks (CNNs). CNNs are one of state-of-the-art image recognition frameworks, and have used the Rectified Linear Unit (ReLU) as the activation function. However, the ReLU rectifies negative values to zero. This paper applies the Sign-to-Position (S/P) format conversion after convolutional procedures to eliminate the rectification loss. Experimental results show that the proposed method improves the recognition accuracy of the MNIST and Fashion-MNIST data set by 0.50% and 1.30% compared with a conventional CNN respectively. The S/P format conversion also contributes to negative image recognition, and results in 12.58% and 3.66% higher accuracy.
ETHICS (Effective Technical and Human Implementation of Computer Based Systems): A human oriented information system development

The policy about teacher professionalism has been applied for last decade in Indonesia.However, science and technology development, changes in society, innovation in teaching and learning theory, and all other changes demand a sustainable teacher empowerment system.Considering this demand, it is necessary for UniversitasNegeri Medan, as an educational institution and also teacher training university, to develop a policy that support the empowerment system of professional teacher.In previous funding term such a system had been developed and one of components of this system is informational system.This article describes an aspect of this informational system development process, which is the development method used to build the informational system.There are many informational system developmental methods available.The question is which one is more suitable for the purpose of empowering teacher sustainably.Considering that the function of the informational system is to connect UniversitasNegeri Medan with the stakeholders including teachers, than the system needs to put importance to the human aspect.Hence the model described in this article is called ETHICS (Effective Technical and Human Implementation of Computer Based Systems).One thatbalances the human and technical aspects in developing the informational system..
Perencanaan Sistem Plambing Air Buangan Gedung Rusunawa Mahasiswa Universitas Andalas

&lt;p&gt;According to Indonesian National Standard (SNI) No.03-7065-2005, the building with more than 500 inhabitants, should prepare plumbing system design. The plumbing sewerage design of student flats building referred to SNI 03-6481- 2000 and SNI 03-7065-2005. Sewerage system for black- and grey water was discharged separately. Black water comes from the closet and the toilet clean out, while grey water comes from the lavatory, sink and floor drain. The wastewater flow rate is determined based on the plumbing fixtures. The sewage flowed partially full in horizontal pipe, and discharged into the standpipe in the the building shaft then flowed to the wastewater treatment plant i.e anaerobic-aerobic bioseptic tank. Grease traps are mounted at the sink to separate oils and fats. Each wastewater fixture is equipped with a fixture vent connected to the standpipe vent which extended through the roof to outdoors. Vent system consists of the vent circuit that connected to the toilet and the floor drain respectively, and the single vent that connected to the sink and the lavatory respectively. Black water sewerage pipes used 3-4 inches PVC, while the grey water sewerages used 1 ½ - 2 ½ inches PVC, and vent used pipe 2-4 inches PVC.&lt;/p&gt;
Management of Postgraduate Library of State Islamic Institute of Kediri in Increasing Students Reading Interest

Abstract: This article aims to examine how the management of the postgraduate library of State Islamic Institute of Kediri (IAIN Kediri) in increasing students reading interest. Technological developments have positive and negative values, especially in relation to reading interest and literacy culture. The convenience offered sometimes causes students’ reluctance to read printed books, which has been the main reference in every lecture. This article is written based on qualitative research in the form of case study, where the object of study, which is the center of discussion, is the IAIN Kediri postgraduate library. The results of the study show that the management of the Postgraduate Library of IAIN Kediri in increasing student-reading interest can be categorized into three forms. The first is to optimize services for the entire Postgraduate academic community, especially in an effort to facilitate the implementation of the Tri Dharma of Higher Education. The second is through layout settings, where it prioritizes the convenience of the academic community when doing activities in the library. Third is the diversification of collections, in which the form of library collections is not limited to collections in printed form but also granting broadest access to the academic community to explore non-printed collections such as journals and proceedings online.
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation

The computational efficiency of approximate Bayesian computation (ABC) has been improved by using surrogate models such as Gaussian processes (GP). In one such promising framework the discrepancy between the simulated and observed data is modelled with a GP which is further used to form a model-based estimator for the intractable posterior. In this article we improve this approach in several ways. We develop batch-sequential Bayesian experimental design strategies to parallellise the expensive simulations. In earlier work only sequential strategies have been used. Current surrogate-based ABC methods also do not fully account the uncertainty due to the limited budget of simulations as they output only a point estimate of the ABC posterior. We propose a numerical method to fully quantify the uncertainty in, for example, ABC posterior moments. We also provide some new analysis on the GP modelling assumptions in the resulting improved framework called Bayesian ABC and discuss its connection to Bayesian quadrature (BQ) and Bayesian optimisation (BO). Experiments with toy and real-world simulation models demonstrate advantages of the proposed techniques.
Recommendation in Dialogue Systems

Author(s): Sun, Yueming | Advisor(s): Zhang, Yi | Abstract: Dialogue system has been an active research field for decades and is developing fast in recent years, due to the recent breakthrough of the deep learning techniques. How to make recommendations in dialogue systems is attracting increasing attention because such systems could meet various user information needs and have much commercial potential.Current dialogue system researches typically focus on building systems for social conversation, question answering, and performing specific tasks. However, making recommendations to users, as important information need, has not been intensively researched. Meanwhile, traditional recommender systems are usually developed for non-conversation scenarios. In this dissertation, we explore how to integrate these two systems into one framework that specifically aims at making recommendations in dialogues. Such a system helps users find items by chatting with users to understand their preferences and recommending accordingly.First, we build conversational recommendation datasets, because existing dialogue datasets do not have user-item preference information or the dialogue utterances discussing facets of items, and current recommendation datasets do not have dialogue scripts associated with each user-item pair. We build the datasets by requesting crowdsourcing workers to compose dialogue utterances based on schemas and then use the delexicalization approach to simulate dialogues with the collected utterances. The datasets are used to train the natural language understanding component and provide recommendation information for our system.Based on collected datasets, we propose a reinforcement learning based conversational recommendation framework. Such a framework has three components, a belief tracker, a dialogue manager, and a recommender. The dialogue agent learns to first chat with a user to understand her preferences, and when it feels confident enough, it recommends a list of items to the user. We conduct both offline and online experiments to demonstrate the effectiveness of the framework.We further extend this framework with a personalized probabilistic recommender module. This recommender learns to predict the probability of a user likes an item given the dialogue utterance information and the personalized user preference information. By leveraging this hybrid information, the recommendation and dialogue performances are further improved. We evaluate the dialogue agent's strength in various simulated environments as well as in online user studies and demonstrate the advantages of this approach.
Autonomous Anomaly Detection System for Crime Monitoring

Autonomous anomaly detection has attracted significant amount of attention in the past decade due to increased security concerns all around the world. The volume of data reported by surveillance cameras has outrun human capacity and there exists a greater need for anomaly detection systems for crime monitoring. This project proposes a solution to this problem in a reception area context by using trajectory analysis. Trajectory extraction is proposed by using Gaussian Mixture Models and Kalman Filter for data association. Then trajectory analysis is performed on extracted trajectories to detect four different anomalies which are entering staff area, running, loitering and squatting down. The proposed anomaly detection method is tested on datasets recorded at Asia Pacific University’s reception area. The proposed algorithms were able to achieve a detection accuracy of 89% and a false positive rate of 4.52%. The results presented show the effectiveness of the proposed method.
Modeling pages left blank in university examination: A resolution in higher education process

Trees are the main sources of paper production, in most of the cases, as far as the intellectual usages are concerned. However, our planet is lacking in that particular natural resource due to rapid growth of population, urbanization, and increased pollution, more importantly non-judicial utilization of such kind. Indian education sectors (schools, colleges, universities) utilize a major part in consumption of papers as a classical practice for conducting examinations and other documentation activities. Our attempt in this article is to investigate and provide an optimal estimate of the number of pages actually required in answer booklet in higher education sector. Truncated Poisson distribution is found to be the best fit for the data on number of pages left blank in an answer booklet after conduction of semester end examinations. To predict the outcome based on various factors such as, lines per pages, words per line, types of examinations etc. suitable regression modeling is performed. A real data set, collected over a period of one month, is been analyzed to illustrate the methods and conclusion is accomplished in the direction of cost reduction, saving of papers, and in turn, logical uses of natural resource to protect environmental interests.
An Analysis on the Blended Teaching Reform on Project Implementation for English Majors in Dalian Neusoft University of Information

In the recent decades, as a member of the international organizations of engineering education, Dalian Neusoft University of Information has introduced the concept of project-based teaching into its curriculum construction.In DNUI, projects have been classified into five different levels in teaching and have been designed for the purpose of cultivating students' comprehensive qualities.The project of Next Stop the World, and the Workplace English Language Project I and II have been designed at the course level and are open to students in their first, second and third practice semesters respectively.With the development of information technology, blended teaching model has gained an increasing popularity among higher educational institutions.The project implementation in DNUI has also taken reforms accordingly.It now focuses on the construction of flexible teaching resources and the design of flipped classroom with pre-class, in-class and after-class activities.So far, the blended teaching model for project implementation has successfully motivated English major students to their full potentials and has made great contribution to the cultivation of professional talents in DNUI.
Go-Byar Based on Virtual Reality for the Learning Media of Gamelan

Gong Kebyar is one of the group of Balinese music that has five pelog tones which the playing technique using kebyar system. Gong Kebyar serves the instrumental performances, accompanying various types of dances, and accompanying Himdu's religious ceremonial activities in Bali. But not many young people can play the gong kebyar due to lack of adequate facilities. One effort that can be done is to utilize virtual reality technology as an instructional media for playing Gong Kebyar. The purpose of the study was to design and implement the design of Gamelan Gong Kebyar based on Virtual Reality.The development of the Gamelan Gong Kebyar Game based on Virtual Reality was implemented using the ADDIE model. The main feature of this game was playing the gamelan Gong Kebyar instrument, besides that there is a feature playing the instrument accompanied by the song so that the player could feel the situation of playing it in form of sekaa. The design is using a functional model which is UML (Unified Modeling Language) and implemented using programming language C# which edited by MonoDevelop-Unity. The results of this study is a Gong Kebyar application based on virtual reality which is operated with a computer and HTC VIVE VR device. All features in this application function properly. With this application, the community can learn to play Gong Kebyar with the results of the user response test obtaining a value of 91%, which means it is included in the excellent category.
Thoughts on the Application of Positive Psychology to Overcoming the Learning Disgust of Middle and Primary School Students

This paper analyzes the tiredness of primary and secondary school students from the perspective of positive psychology.Positive psychology mainly includes four aspects: positive thinking, positive emotional experience, positive quality and positive social environment.The enlightenment of positive psychology on overcoming the anorexia in primary and middle schools :(1) Learning to make positive cognition of problems; (2) Cultivate the positive emotions of misogynistic experience: Use intuitive and experiential teaching to stimulate learning interest; Use the principle of "nearest development area" to let them experience the sense of achievement.Give positive evaluation in time to enhance their confidence; Leads to correct attribution, stimulates the learning motivation.(3) Cultivate the misogynist with such positive qualities as diligence, optimism and persistence; (4) Create a loose and harmonious social environment for misogynists.
ORDINE DELLA NATURA E FIGURE DELLA VERITÀ

The human knowledge and the order of nature: the problem of their relationship is the core of paper. The solution concerns the co-operation between the instrumental and technological knowledge and the sociale work of language.
VATEX Captioning Challenge 2019: Multi-modal Information Fusion and Multi-stage Training Strategy for Video Captioning

Multi-modal information is essential to describe what has happened in a video. In this work, we represent videos by various appearance, motion and audio information guided with video topic. By following multi-stage training strategy, our experiments show steady and significant improvement on the VATEX benchmark. This report presents an overview and comparative analysis of our system designed for both Chinese and English tracks on VATEX Captioning Challenge 2019.
Internet of Things (IoT), PBL and 3D Holographic modelling for smart agricultural education at the University of Queensland

The project described in this paper builds on exciting technological developments in real time biophysical data gathering that are currently happening at The University of Queensland (UQ)'s regional campus (UQGatton ~1000ha of prime agricultural land ~85km SW of Brisbane in SE Queensland), via the Internet of Things (IoT) UQ Smart Campus Project. This paper will describe the development of multifaceted web-based interfaces, problem based learning modules, and 3D modelling using the real time streaming data acquired through the Internet of Things (IoT) technology of the UQGatton Smart Campus Initiative. The idea is to produce innovative teaching and assessment modules for multiple different courses in the UQ Science Faculty, and across 2 Campuses separated by 85kms of highway. The paper describes the technology involved, the challenges and workarounds and a number of examples of using the data collected for problem-based learning modules. Some discussion is included on what these technologies could provide for further Teaching & Learning developments in the “E” space being trialed with partners UQ ITS, Microsoft and Telstra/Readify.
The Effect of Learning Model and Motivation Level on Students’ Self-Eficacy

Self-Efficacy is a person's belief on his ability to complete certain tasks. The purpose of this study was to determine the influence differences between two learning models, namely TPSR and Cooperative Learning on students who have high and low motivation levels to increase self-efficacy of the fifth grade students. Experimental methods with 2x2 factorial design was used. The sample of this research were105 fifth grade students at SDN 208 Luginasari, Bandung, chosen by using total sampling technique. Data analysis used SPSS version 21 with hypothesis testing through Two Way Anova. The results of the analysis and calculation of the data revealed that; there was no significant difference in the effect between the two learning models on increasing students’ self-efficacy; there was an interaction between learning models with motivation towards increasing self-efficacy; there was no significant difference in the effect between the two learning models with high levels of motivation towards the increase of self-efficacy; and there was no significant difference in the effect between the two learning models with low motivation levels on increasing self-efficacy. The conclusion of this study is that both of the learning models have the same effect on both high and low motivation levels on the student self-efficacy and there is an interaction between learning models and motivation on increasing the student self-efficacy.
Supervised feature selection with orthogonal regression and feature weighting

Effective features can improve the performance of a model, which can thus help us understand the characteristics and underlying structure of complex data. Previous feature selection methods usually cannot keep more local structure information. To address the defects previously mentioned, we propose a novel supervised orthogonal least square regression model with feature weighting for feature selection. The optimization problem of the objection function can be solved by employing generalized power iteration (GPI) and augmented Lagrangian multiplier (ALM) methods. Experimental results show that the proposed method can more effectively reduce the feature dimensionality and obtain better classification results than traditional feature selection methods. The convergence of our iterative method is proved as well. Consequently, the effectiveness and superiority of the proposed method are verified both theoretically and experimentally.