Reviewerly/exHarmony huggingface dataset:
Improving Extreme Learning Machine by a Level-based Learning Swarm Optimizer and its Application to Fault Diagnosis of 3D Printers

Fault diagnosis plays a significant role in the printing quality for 3D printers.In this paper, an extreme learning machine based on levelbased learning swarm optimizer (LLSO-ELM) is proposed to diagnose faults of delta 3D printers.Extreme learning machine (ELM) achieves better performance in learning speed than traditional gradient descent algorithms.However, the random inputs weights and hidden biases are influential factors for the accuracy and generalization performance of ELM.LLSO has competitive performance in solution quality and computational efficiency for large scale optimization problems, and it is used to obtain the optimum configuration of the weights and biases for ELM.The proposed model is tested by using the attitude data of a delta 3D printer under different operating modes.The experimental results verify that the proposed approach performs better in generalization and stability than ELM.
Development of Lesson Plan (LP) with Software Lectora Inspire Assisted Problem-Based Learning in Improving Learning Outcomes for Senior High School

This research-based on technological advances that promote the use of technology in learning, on the lack of valid, practical and effective lesson plans, particularly in problem-based learning models that are in line with the 2013 curriculum, and on the use of Lectora Inspire Software in the creation of lesson plans. This study was conducted to develop a product that is a problem-based learning model based on Lectora Inspire software, and that is valid, practical and effective. This type of research is research and development (research and development). The design of this study based on 5 out of 10 phases of Borg and Gall's research design, namely research and collection of initial information, planning, development of original product formats, initial testing and product improvement. The effectiveness test results were rated as very good if the results of the analysis of the responses of teachers and students with an average of 88% and 89.04% as and the increase (n-gain) of student learning outcomes is 0.62 which can be categorized as a moderate increase.
An Empirical Study of Content Understanding in Conversational Question Answering

With a lot of work about context-free question answering systems, there is an emerging trend of conversational question answering models in the natural language processing field. Thanks to the recently collected datasets, including QuAC and CoQA, there has been more work on conversational question answering, and recent work has achieved competitive performance on both datasets. However, to best of our knowledge, two important questions for conversational comprehension research have not been well studied: 1) How well can the benchmark dataset reflect models' content understanding? 2) Do the models well utilize the conversation content when answering questions? To investigate these questions, we design different training settings, testing settings, as well as an attack to verify the models' capability of content understanding on QuAC and CoQA. The experimental results indicate some potential hazards in the benchmark datasets, QuAC and CoQA, for conversational comprehension research. Our analysis also sheds light on both what models may learn and how datasets may bias the models. With deep investigation of the task, it is believed that this work can benefit the future progress of conversation comprehension. The source code is available at https://github.com/MiuLab/CQA-Study.
Denoising performance analysis of adaptive decision based inverse distance weighted interpolation (DBIDWI) algorithm for salt and pepper noise

&lt;p&gt;Due to its superior performance for denoising an image, which is contaminated by impulsive noise, an adaptive decision based inverse distance weighted interpolation (DBIDWI) algorithm is one of the most dominant and successful denoising algorithm, which is recently proposed in 2017, however this DBIDWI algorithm is not desired for denoising the full dynamic intensity range image, which is comprised of min or max intensity. Consequently, the research article aims to study the performance and its limitation of the DBIDWI algorithm when the DBIDWI algorithm is performed in both general images and the images, which are comprised of min or max intensity. In this simulation experiments, six noisy images (Lena, Mobile, Pepper, Pentagon, Girl and Resolution) under salt&amp;amp;pepper noise are used to evaluate the performance and its limitation of the DBIDWI algorithm in denoised image quality (PSNR) perspective.&lt;/p&gt;
Large-scale image-to-video face retrieval with convolutional neural network features

Convolutional neural network features are becoming the norm in instance retrieval. This work investigates the relevance of using an of the shelf object detection network, like Faster R-CNN, as a feature extractor for an image-to-video face retrieval pipeline instead of using hand-crafted features. We use the objects proposals learned by a Region Proposal Network (RPN) and their associated representations taken from a CNN for the filtering and the re-ranking steps. Moreover, we study the relevance of features from a finetuned network. In addition to that we explore the use of face detection, fisher vector and bag of visual words with those CNN features. We also test the impact of different similarity metrics. The results obtained are very promising.
User-centered personas for PhysPort

PhysPort is a professional development website for physics faculty to develop their teaching through research-based resources.As part of PhysPort's ongoing research efforts, we conducted interviews with 23 physics faculty from diverse instructional and institutional contexts in the US.From our interviews, we sought common experiences, motivations, and pain points to develop personas-person-like constructs-of physics faculty in the US.Our research focuses on the perspectives of the key users of our site, and thus we take a user-centered perspective rather than a researcher-centered perspective.We developed personas, which are person-like constructs that are developed based on salient characteristics of actual users, that enable designers to create resources to meet actual user needs without designing for the idiosyncrasies of specific users.We present our set of six personas of physics faculty members: a faculty member who is new to improving his teaching; one who takes up his department's practices; one who wants her teaching to feel good; one who is comfortable in her teaching; one who is continuously improving; and one who solves big problems in her department.These personas of physics faculty making changes to their teaching can be used more broadly to improve the design and development of professional development resources and activities for physics faculty.
"FORMATION OF A PROFESSIONAL WORLDVIEW OF A PHYSICS TEACHER IN A STEM-ORIENTED EDUCATIONAL ENVIRONMENT"

The article presents the results of a study of the professional worldview of physics teacher. It has been determined that there are many interpretations of the concept of the worldview. The ambiguity of the interpretations leads to an unclear understanding of the components of the worldview by representatives of different industries. The analysis allows to identify three main aspects that form the professional worldview of physics teacher. Among the factors that influence the development of the professional thinking of the teacher are the innovative learning technologies, which the leading modern technology is STEM. The introduction of such technologies in the educational process of secondary education institutions requires a modern physics teacher to acquire appropriate methodological competences, as well as special knowledge and skills at all stages of technology implementation. It has been determined that the modern teacher must have certain personality traits that allow him to successfully innovate: communication, cooperation, critical thinking, creativity. The article proves that preparation of physics teacher based on the selected principles will help to form his professional worldview.Keywords: worldview, pedagogical worldview, professional worldview of the teacher, physics learning, integration, STEM education, learning environment.
DEVELOPMENT OF PEDAGOGICAL MASTERY OF FUTURE VOCATIONAL TRAINING TEACHERS UNDER CONDITIONS OF EDUCATIONAL TRANSFORMATIONS

The problem of pedagogical skills of the future teacher of professional training formation is analysed in the work presented.The necessity as for the development of the quality is primarily due to the needs of the labour market for new education pedagogues possessing and revealing critical thinking, communication skills, digital competence, etc.The authors summarize in the idea concerning the following fact that the teacher-master is a highly-developed personality, a specialist of high culture, a master of one's work, who posessing perfect psychological knowledge, awareness in various fields of science and art, mastery in the subject he teaches, training and upbringing skills.The objective of the article is to reveal some peculiarities concerning the ways of development of future teachers of vocational training pedagogical skills in the educational process of Oleksandr Dovzhenko Hlukhiv National Pedagogical University.The authors believe that the quality can be improved when the appropriate environment is created.The development of the specified quality is carried out by means of involving teachers and students in the activities provided by scientific laboratory «Innovative training technologies», performing researches and studies within the initiatiated research theme of the work of the department «Pedagogical mastery of the teacher of vocational training development under conditions of educational transformations» and training
PERANCANGAN SISTEM INFORMASI WORK ORDERDENGAN METODE ITERATIF MENGGUNAKAN FRAMEWORK CODEIGNITER (Studi Kasus :CV Sirna Miskin Bandung)

This research was aimed to know the current of Work Order Information System at CV Sirna Miskin Bandung, to find out the problems facing, and to know how to cope these problems. Based on the research result, it turns out that the problems of work order data processing is still manual by using Spreadsheet application, so that the detail information of work order such as status, work duration, who’s working on it and report processing became slower and less accurate.To resolve these problems, it is neccessary work order information system design with an integrated database was needed for simplify the process of managing data, so that the information needed an report processing became faster, complete and precise.Data collection methods was using observation, interview and literature study, while the method of this information system design was using object oriented method with the UML (Unified Modelling Language) and implemented using framework PHP Codeigniter and MySQL as database. Iteration method was used as for the software development.The suggestion given is : 1) Perform maintenance, develop, and update to the system which designed sustainably, 2) Developing system to becomes larger by including other business process, 3) Create system for mobile version to improve accessibilty.
Informational and Psychological Influence on Student Youth in the Conditions of the Information-Psychological War

Peculiarities of informational and psychological influence on social consciousness as a destructive tool in the conditions of conducting the information-psychological war are considered in the article. The danger of informational and psychological influence on the citizens’ consciousness is that such influence changes the normal behavior of people, their reactions to the surrounding world. It makes the person's psyche vulnerable and encourages the individual to destructive actions against society. This is a danger not only for the psychological state of an individual member of society, but also for the whole country. The purpose of the study is to reveal the peculiarities of informational and psychological influence on social consciousness in the conditions of the information-psychological war. The research was conducted using the following methods: methods of mathematical statistics, experiment, prosopographical method. It was proved that the verification of information received from the media is not verifiable by representatives of student youth on the basis of the survey. Informational and psychological influence is an important tool for conducting the information-psychological wars and operations. It is seriously detrimental to social consciousness. Young people need special protection because the future of the country depends on them. It is noted that there is a need to develop mechanisms for protecting young people from negative informational and psychological influence. The media must submit proven information in a dosed form using a simple vocabulary. Government agencies should develop rules of work in the Internet space of the state, which will help to protect society as a whole, and student youth in particular, from the negative informational and psychological influence.
Comparative analysis of databases working under the control of Windows system

The aim of this paper is to conduct research on the most popular database management systems such as MySQL, PostgreSQL and Firebird in terms of query performance, CPU load and disk usage. At the first stage, the analysis of the popularity of databases was carried out. In the second stage an application was created that allows for communication with selected databases. At the third stage, tests were carried out using a written application and analysis of results.
Exploring the Essentials and Principles of Software Development

There is utmost pressure on software development industry to build quality software's as we have become highly dependent on software's directly or indirectly.Software development has many phases like testing which requires the maximum time as well as resources like human efforts and investment.The time required for completion of software testing is more than the time required to complete all remaining phases of software development.The quality of software heavily depends on quality of software testing process.Therefore, Software testing can be considered as necessary evil for verifying the software quality.This paper discusses some of the most critical aspects and principles of software development and testing.
A Division Algorithm in a Redundant Residue Number System Using Fractions

The residue number system (RNS) is widely used for data processing. However, division in the RNS is a rather complicated arithmetic operation, since it requires expensive and complex operators at each iteration, which requires a lot of hardware and time. In this paper, we propose a new modular division algorithm based on the Chinese remainder theorem (CRT) with fractional numbers, which allows using only one shift operation by one digit and subtraction in each iteration of the RNS division. The proposed approach makes it possible to replace such expensive operations as reverse conversion based on CRT, mixed radix conversion, and base extension by subtraction. Besides, we optimized the operation of determining the most significant bit of divider with a single shift operation of the modular divider. The proposed enhancements make the algorithm simpler and faster in comparison with currently known algorithms. The experimental simulation using Kintex-7 showed that the proposed method is up to 7.6 times faster than the CRT-based approach and is up to 10.1 times faster than the mixed radix conversion approach.
Joint Inpainting of RGB and Depth Images by Generative Adversarial Network with a Late Fusion Approach

Image inpainting aims to restore texture of missing regions in scene from an RGB image. In this paper, we aim to restore not only the texture but also the geometry of the missing regions in scene from a pair of RGB and depth images. Inspired by the recent development of generative adversarial network, we employ an encoder-decoderbased generative adversarial network with the input of RGB and depth image. The experimental results show that our method restores the missing region of both RGB and depth image.
Disentangling Representations using Gaussian Processes in Variational Autoencoders for Video Prediction

We introduce MGP-VAE (Multi-disentangled-features Gaussian Processes Variational AutoEncoder), a variational autoencoder which uses Gaussian processes (GP) to model the latent space for the unsupervised learning of disentangled representations in video sequences. We improve upon previous work by establishing a framework by which multiple features, static or dynamic, can be disentangled. Specifically we use fractional Brownian motions (fBM) and Brownian bridges (BB) to enforce an inter-frame correlation structure in each independent channel, and show that varying this structure enables one to capture different factors of variation in the data. We demonstrate the quality of our representations with experiments on three publicly available datasets, and also quantify the improvement using a video prediction task. Moreover, we introduce a novel geodesic loss function which takes into account the curvature of the data manifold to improve learning. Our experiments show that the combination of the improved representations with the novel loss function enable MGP-VAE to outperform the baselines in video prediction.
A dynamic perspective on L2 pronunciation development: bridging research and communicative teaching practice

The main goal of this paper is to raise language teachers’ awareness of the need to incorporate research-based pronunciation teaching into their communicative language classes in an ongoing and integrated manner. To do so, we begin by characterizing language and its learning process as dynamic systems, which develop over time through the constant interaction of their agents. Then we review current studies on L2 sound production and perception as well as on the explicit teaching of L2 pronunciation under a dynamic perspective in the Brazilian scenario. Finally, we suggest a few general directions and guiding principles for pronunciation teaching, showing that it is possible to include pronunciation instruction in communicative language teaching.
Predicting the Physical Dynamics of Unseen 3D Objects

Machines that can predict the effect of physical interactions on the dynamics of previously unseen object instances are important for creating better robots and interactive virtual worlds. In this work, we focus on predicting the dynamics of 3D objects on a plane that have just been subjected to an impulsive force. In particular, we predict the changes in state-3D position, rotation, velocities, and stability. Different from previous work, our approach can generalize dynamics predictions to object shapes and initial conditions that were unseen during training. Our method takes the 3D object's shape as a point cloud and its initial linear and angular velocities as input. We extract shape features and use a recurrent neural network to predict the full change in state at each time step. Our model can support training with data from both a physics engine or the real world. Experiments show that we can accurately predict the changes in state for unseen object geometries and initial conditions.
HOW THE FINANCIAL OPENNESS ACCELERATES THE ECONOMIC GROWTH OF LEADING ASEAN ECONOMIES

This research study has given important implications for regulators through elaborating the association between economic growth, financial openness among the five member countries of ASEAN including Philippines, Indonesia, Thailand, Malaysia, and Singapore.An insight has been provided about the relation of economic growth and trade openness from the practical aspect in ASEAN economies.Therefore, the policy makers are supported through this information to develop, overview, and revise the existing regulations and policies of financial openness.This research study has made significant contributions through analyzing the association between economic growth and financial openness from the theoretical aspect.The study has argued that the current literature is extended by this study through focusing on the developing economies of ASEAN.Banking sector is a crucial institution for any economy and economic growth is negatively influenced through collapse of the banking activities.Further, financial system comes at risk through financial openness, but it has a considerable role in the development of economies.The financial system liberalization is the main factor, which drives economic growth among the ASEAN countries.There is need for the policy makers to review and alter the existing regulations of financial openness.
Common Representational Model and Ontologies for Effective Law Enforcement Solutions

Ontologies have developed into a prevailing technique for establishing semantic interoperability among heterogeneous systems transacting information. An ontology is an unambiguous blueprint of a concept. For Artificial Intelligence, only the defined notions can be considered existent. Thus, in relation to AI, an ontology can be understood as part of a program which delineates a collection of descriptions. An ontology, therefore, correlates the labels of the entities in the universe of discourse with wording that holds meaning for humans, explaining what those labels signify, along with the precise principles that force the interpretation and semantic utilization of these labels. An ontology constitutes a proper statement of a logical theory. It is a crucial component of a system with the capability to process, manage, analyze, correlate and reason from the large datasets characterized by heterogeneity. This paper depicts the process of development of a Common Representational Model (CRM) on top of several ontologies, taxonomies and classifications to facilitate computational and data mining functionalities. The building blocks of said CRM are delineated in detail, as well as its application in a specific use case.
Telecytology for Rapid On-Site Evaluation

Telecytology is the method of interpreting cytology material from a distance using digital representation for cytology evaluation. Pioneering efforts have been underway for over a decade to introduce telecytology into clinical practice. The field of telecytology has been evolving and many of the prior technologies are rapidly becoming outdated. With such expansion, the current applications of telecytology are increasing for clinical practice, quality assurance, education, and research. Although the literature for digital telecytology is relatively scant, this highlights the unique challenges in relation to telecytology platforms, use cases, implementation, and validation. Several modes of telecytology exist, including static (store-and-forward), dynamic (live video streaming), robotic microscopy, whole-slide imaging, or hybrid technology. Considerations for telecytology include understanding the people, processes, and technology in considering and deploying a telecytology system. Challenges when implementing telecytology specific for rapid on-site evaluations (ROSE) may include cost analysis and administrative buy-in, workflow assessment, training, and staffing (i.e., cytotechnologists, trainees, cytopathologists), as well as technical difficulties. Each implementation will be dependent on the intended use case and need for adoption. This chapter covers all of the aforementioned aspects of telecytology for ROSE.