Reviewerly/exHarmony huggingface dataset:
A Refection on Digitalized Creation of Chinese Internet Big Movies in the Context of Internet

The 21st century is the era of the Internet, where movies see new vitality in artistic creation under the concept of the Internet+. Internet Big movies, a new type of films born with the advancement of Internet technology, have seen rapid development in less than a decade, having gradually established a mature production model. This paper provides reflection and analysis on the new phenomena in Chinese film production that involve numerous applications of big data technologies.
Fast Doesn’t Mean Bad. Express Reprocessing and Reinterpretation of Retro Data from Seismic Survey 2D

Summary Within the framework of this work, the results of reprocessing and interpretation of seismic survey 2D of the 1980–1988 seasons, at the licensed area of PJSC Gazprom Neft, obtained in a short time to reduce geological and economic risks and refine the assessment of the resource base, are presented.
Multilingual Counter Narrative Type Classification

The growing interest in employing counter narratives for hatred intervention brings with it a focus on dataset creation and automation strategies.In this scenario, learning to recognize counter narrative types from natural text is expected to be useful for applications such as hate speech countering, where operators from non-governmental organizations are supposed to answer to hate with several and diverse arguments that can be mined from online sources.This paper presents the first multilingual work on counter narrative type classification, evaluating SoTA pre-trained language models in monolingual, multilingual and cross-lingual settings.When considering a fine-grained annotation of counter narrative classes, we report strong baseline classification results for the majority of the counter narrative types, especially if we translate every language to English before cross-lingual prediction.This suggests that knowledge about counter narratives can be successfully transferred across languages.
Gaussian Process Self-triggered Policy Search

In this paper, we propose a policy search reinforcement learning method with a non-parametric policy model and self-triggered control. We formulate a self-triggered policy search that employs a control policy and an execution length policy to reduce the number of action decisions in a trial. Our method employs sparse Gaussian process as a policy model with a self-triggered control framework, and its update law for maximizing return is derived based on variational Bayesian learning. We conducted simulations for a reaching task in a two-dimensional environment and confirmed the effectiveness of our proposed method.
Mobile Manipulator!s Movement along B-spline Curve to Wipe Curved Objects

Robotic vacuum cleaners have become widespread to sweep the floor. It is important to wipe objects on the floor to clean the house up, but there are some curved objects such as a toilet bowl or a kitchen sink. If the curved surface of an object can be expressed mathematically, the trajectory to wipe the surface will be obtained. In this research, a mobile manipulator with an RGB-D camera was selected to collect point cloud data and handle cleaning tools. The point cloud model of a toilet bowl was created, and the trajectory using a B-spline curve was generated. In experiments, Toyota ’s Human Support Robot was used, and the cleanness of the toilet bowl was evaluated by reference to the rule of a robot competition (i.e., World Robot Summit). As a result, the authors confirmed that the scrubbing movement, part of the wiping movement, should be improved.
Machine Learning

Machine learning (ML) is a data-driven modeling approach that has become popular in recent years, thanks to major advances in software and hardware. Given enough data about a complex system, ML allows a computer model to imitate that system and predict its behavior. Unlike a deductive modeling approach, which requires some understanding of a system to be able to predict its behavior, the inductive approach of ML can predict the behavior of a system without ever understanding it in a traditional sense. Climate is a complex system, but there is not enough observed data describing an unprecedented event like global warming on which a computer model can be trained. Instead, it may be more fruitful to use ML to imitate a climate model, or a component of it, to greatly speed up computations. This will allow the parameter space of climate models to be explored more efficiently.
Concluding Thoughts

Throughout this fourth and final book of the Routledge Focus on Team Academy series, stories of research and practice have emerged focused on how TA has inspired people and how it has been implemented in different contexts, including outside traditional TA-based settings. What follows is an amalgamation of a number of conversations that have taken place over the development of the Team Academy in Diverse Settings book, along with responses to some questions about what from TA attracted them, the place and the context in which the authors were operating, what they have learnt throughout their TA journey, the impact and legacy that TA left on them and where they think TA should go next. The emerging conversations in this chapter offer an indication of some of the contributors’ thoughts about the model and approach.
The Wave Equation

Taking the continuum limit of the chains of masses from the previous chapter, we arrive at the wave equation, the physical subject of this chapter. The connection to approximate string motion is an additional motivation. Viewed as a manifestation of a conservation law, the wave equation can be extended to other conservative, but nonlinear cases, like traffic flow. Mathematically, we are interested in turning partial differential equations (PDEs) into ODEs, making contact with some familiar examples. Making PDEs into ODEs occurs in a couple of ways --- the method of characteristics, and additive/multiplicative separation of variables are the primary tools.
Entity Manager

Entities do not persist themselves when they are created. Nor do they remove themselves from the database when they are garbage-collected. It is the logic of the application that must manipulate entities to manage their persistent lifecycle. Jakarta Persistence provides the EntityManager interface for this purpose in order to let applications manage and search for entities in the relational database.
Introducing Language Analysis

This is an engaging introduction to the study of language for undergraduate or beginning graduate students, aimed especially at those who would like to continue further linguistic study. It introduces students to analytical thinking about language, but goes beyond existing texts to show what it means to think like a scientist about language, through the exploration of data and interactive problem sets. A key feature of this text is its flexibility. With its focus on foundational areas of linguistics and scientific analysis, it can be used in a variety of course types, with instructors using it alongside other information or texts as appropriate for their own courses of study. The text can also serve as a supplementary text in other related fields (Speech and Hearing Sciences, Psychology, Education, Computer Science, Anthropology, and others) to help learners in these areas better understand how linguists think about and work with language data. No prerequisites are necessary. While each chapter often references content from the others, the three central chapters on sound, structure, and meaning, may be used in any order.
Experiment for measuring position error in a mobile robot with mecanum wheel

It is difficult for mobile robot to estimate accurate localization by odometry. In particular, it is difficult for omni-directinal mobile robot to estimate accurate localization by odometry. Position error of mobile robot is mainly because of slips on the wheels. Therefore, each angular velocity is compensated the error of the velocity of the mobile robot that calculated by introducing the error coefficient. The purpose of the research is to aim for autonomaous movement and map generation in an environment including dynamic obstacles using omni-directional mobile robot with mecanum wheel. In this paper, we investigate in order to give an error confident, we consider the tendncy of the measurement error of the same mobile robot with mecanum wheel in the actual environment.
A new framework for Person Re-identification: Integrated level feature pattern (ILEP)

The system for re-identifying persons is used to find and verify the persons crossing through different spots using various cameras.Much research has been done to re-identify the person by utilising features with deep-learned or hand-crafted information.Deep learning techniques segregate and analyse the features of their layers in various forms, and the output is complex feature vectors.This paper proposes a distinctive framework called Integrated Level Feature Pattern (ILFP) framework, which integrates local and global features.A new deep learning architecture named modified XceptionNet (m-XceptionNet) is also proposed in this work, which extracts the global features effectively with lesser complexity.The proposed framework gives better performance in Rank1 metric for Market1501 (96.15%),CUHK03 (82.29%) and the newly created NEC01 (96.66%) datasets than the existing works.The mean Average Precision (mAP) calculated using the proposed framework gives 92%, 85% and 98%, respectively, for the same datasets.
Repairing Windows Startup Problems

In Chapter 8 , I showed you how you can use the tools and utilities available in Windows 10 to troubleshoot startup problems. But what happens if Windows cannot be easily or automatically repaired? If you can’t get your copy of Windows 10 to boot to the desktop, then you can’t get any work done at all.
Generating Collective Behavior of a Robotic Swarm by using Deep Neuroevolution with LSTM

Deep Neuroevolution is a method of optimizing a Deep Neural Network (DNN) using evolutionary computation. By applying this approach for designing the robot controller, the robotic swarm is able to generate collective behavior from raw image inputs. However, we need to explore how to set up the structure of DNN and how theses settings affect the performance. In this paper, we applied DCNN and DCRNN to the controller of a robotic swarm. DCNN is a DNN that can automatically extract image features. DCRNN is a combination of DCNN and Long Short-Terms Memory network. We discussed the performance of DCNN and DCRNN in a two-target area navigation task under the environments with and without an obstacle. The results showed that DCRNN recorded better performance than DCNN in two both environments.
CIS Publication Spotlight [Publication Spotlight]

Presents summaries of recent books published in the field of computational intelligence.
A Proficient Technique for Extraction the High Average-Utility Itemsets with Enhanced Bounds From Transactional Database

HUIM has turned into a well known knowledge extraction, as it can uncover designs that have a highutility, conversely to continuous example extraction, which spotlights on finding incessant examples. High average-utility itemset extraction (HAUIM) is different with HUIM gives an elective quantify, called the average utility, to choose designs by considering their utilities and lengths. In the most recent decades, a few calculations have been created to mine HAUIs. However majorly it takes lot of memory and time, since they for the most part use the average-utility upper-bound model to miscalculate the average utilities of itemsets. To enhance HAUIM here proposes four average utility upper bounds, in view of structure database portrayal, and three proficient prune techniques. Furthermore, a novel conventional system for looking at average-utility upper-bounds is displayed. In view of these theoretical outcomes, a proficient calculation named dHAUIM is presented for extraction the total arrangement of HAUIs. dHAUIM speaks to the inquiry space and rapidly process upper-bounds utilizing a novel IDUL structure. Broad investigations demonstrate that dHAUIM beats three algorithms for extraction HAUIs as far as runtime on both reality and artificial databases.
Blindness to Modality Helps Entailment Graph Mining

Understanding linguistic modality is widely seen as important for downstream tasks such as Question Answering and Knowledge Graph Population.Entailment Graph learning might also be expected to benefit from attention to modality.We build Entailment Graphs using a news corpus filtered with a modality parser, and show that stripping modal modifiers from predicates in fact increases performance.This suggests that for some tasks, the pragmatics of modal modification of predicates allows them to contribute as evidence of entailment.
AN EDUCATIONAL GAME APPLICATION TO ASSIST THE COMMUNITY IN REMEMBERING ROAD DIRECTIONS AND PLACES IN PALEMBANG

Visuospatial processing is one of the important aspects of everyday life, whether it is to travel or to recognize the location of objects around. Visuospatial processing can be improved in various way, one of which is by using repetition. WorldVenture app was created to help its users improve their visuospatial capability by remembering landmarks in the city where they live. WorldVenture was created using flutter framework with five steps, namely literature study, data and information collection, application designing, testing, and evaluation. This app will have three main features: Flashcard, Quiz, and Notes. WorldVenture testing result, using questionnaires, showed 64,5% people out of 30 respondents rated WorldVenture excellent for improving visuospatial capabilities and as many as 35.5% of respondents rated it good.
AUTOMATION OF SHEET METAL COMBINATION DIE DESIGN PROCESS

This paper proposed a novel methodology for designing and manufacturing of sheet metal dies based on features of sheet parts. Also, combination is designed according to die cupping and punching features of sheet metal parts. The proposed approach is an attempt to make seamless integration of computer aided design with computer aided manufacturing. The features used in this study are taken from MusumiTM Catalogue as well as from various small and medium scale sheet metal industries. Work is divided into two phases. In the first phase, the relevant geometrical and topological data is extracted by reading STEP AP 203. In the second phase, a combine adjacency matrix and rule-based system is developed to recognize sheet metal features for die manufacturing. The system showed excellent performance for all types of features contained in the MusumiTM catalog and for different sheet metal industries. The proposed system for automated design of combination dies for sheet metal parts has been tested successfully for various types of industrial deep drawn parts. It reduces the die compoment design time from hours to minutes. selection of die components and drawings generated by the system were found to be reasonable and very similar to those actually used in the sheet metal industries for production of these typical components on combination dies.
The Crucial of Students’ Self-Actualization in Teacher Talk Framework to Increase the Students Speaking Skill

Every teacher should have an appropriate teaching method, including speaking. One of the indispensable parts of foreign language teaching, especially in speaking skills, is teacher talk. Students need teacher talk that is elaborated with the entire self-actualization in increasing their speaking skill. The research was intended to know how the teacher talk's theoretical framework used by the teacher to increase students self-actualization in speaking performance. This research was descriptive qualitative research because it described teacher talk between the teacher and students in the classroom. The data collection instruments were observation and interview. This research showed that students are more active in expressing their ideas, and the classroom was more harmonious. Some of them also were more confident to convey information to the teacher without asked. It can be concluded that teacher talk is essential in increasing self-actualization to get better performance in speaking English.
Peer review declaration

Abstract • Type of peer review: Single-blind/Double-blind/Triple-blind/Open/Other (please describe): Double Blind a. All papers submitted were checked their similarity index using Turnitin. b. Papers have similarity index more than 25% were rejected. c. After that, the format of the papers was checked. Papers that did not follow the IOP template will be sent back to the authors for revision. d. All papers passed the similarity index and have already follow the IOP template will be sent to the reviewers. e. Reviewers reviewed the papers and give comments to the papers. f. Scientific committee decided if the papers: accepted, accepted with major revision, accepted with minor revision, or rejected. g. Author revised their papers and send back their revision h. After that editor will check again using Turnitin to make sure similarity source not more that 5% for each source in each article i. Editor will check again manual to see similarity index and source to make sure all is good • Conference submission management system: All papers from the conference submitted using our system where each author must register first and send article through email vicest@konferensi.id • Number of submissions received: 256 Submission were received • Number of submissions sent for review: 227 Submission was sent for review, and the rest was rejected because out of scope, low-quality article and high similarity • Number of submissions accepted: 147 Paper accepted based on IOP JPCS Scope and quality • Acceptance Rate (Number of Submissions Accepted/Number of Submissions Received X 100): (147/227) x 100 = 64.7 % • Average number of reviews per paper: 2 Times • Total number of reviewers involved: 10 Reviewer Involved+ 5 Editors, each reviewer received 8-10 papers with 2 weeks review process • Any additional info on review process: NONE • Contact person for queries: Robbi Rahim, Sekolah Tinggi Ilmu Manajemen Sukma, Medan, Indonesia and University Malaysia Perlis, Malaysia Email: robbirahim@ieee.org, Whatsapp+62 8126326393
Research of the business process of formation of the teacher's rating with its following analysis

The article examines the subject area of the enterprise associated with the formation of the teacher's rating, namely, the collection of the necessary data by the teacher and the compilation of tables on their activities based on them. The problems of the speed of collection and transformation of information, the infiuence of the human factor on the accuracy of the information provided are highlighted. The purpose of the study is to increase the teacher's efficiency by reducing the labor intensity of the annual reporting process and monitoring his scientific activities. All studies were carried out on the basis of an analysis of the literature on the topic of rules, requirements and regulations for compiling a teacher's rating, an analysis of the accompanying management documentation of universities on the rating assessment of teachers' activities. The result of the research is the solution of the discovered problems, by automating data collection using the api of electronic library services, or parsing them. The field of application of the results is the use of the proposed solution in higher educational institutions of Russia. As part of the application of the proposed solution, it was possible to reduce the amount of time required to collect information about teaching activities for the reporting period by at least thirty percent.
The Framework of Model Explanations

The last few chapters introduced the machine learning domain, the importance of interpretability, and the taxonomy of interpretability methods. The previous chapters introduced machine learning interpretability and focused on general overview and definitions. This chapter discusses the different frameworks of model explanations. Because there are a variety of methods under each category, please refer to the upcoming chapters for a detailed review of how each method works, along with some working versions of the code.
Information and Communication Technologies in the Daily Life of Elementary School Teachers: An Attitudinal Framework

Within the framework of the inclusion of Information and Communication Technologies (ICTs) in primary education classrooms in the City of Toluca, State of Mexico, this research proposes an analysis on the social construction of meaning that teachers make about technology. The focus is mainly on the universe of meaning in which teachers relate to technology, for which it is sought to obtain from teachers a story about how ICT is meant by them. This communication deals in particular with the element that precedes the possible action and thought around any entity in the universe of meaning: attitude. For the formation of our attitude towards an entity, favorable or not, positive or negative, a previous representation of it is required. The analysis is developed under the structure of three general indicators: What do you think about the technologies? Do you like to use technologies in your daily life? and Do you like to work with technologies?
Comparison Experiment of Perceptual Intensity of Jerkiness in Response to Frame Rate Decreasing in Visual Stimuli by using HMD

Recently, VR(virtual reality) technology is widely used for game, amusement and simulation of special experiences etc. by using HMD(Head Mounted Display). High quality of VR content is also needed to increase the reality of experience. However, it also requires to maintain the balance between huge amount of data and its processing cost. As a result, imbalance of them makes the decreasing of frame rate of the VR movie and its smoothness lost. This smoothness lost is called jerkiness and the its relations with motion sickness have been examined by the movie on the flat display in the previous studies. In this study, the experiments by using HMD were conducted to investigate the jerkiness perceptual intensity under the several conditions of the decreasing of frame rate. In this report, the subjective evaluation results by questionnaire survey with subject people have been discussed.
1915թ. ԻՐԱԴԱՐՁՈՒԹՅՈՒՆՆԵՐԻ ՎԵՐԱԲԵՐՅԱԼ ԱՄԵՐԻԿՅԱՆ ՊԱՇՏՈՆԱԿԱՆ ՀԱՅՏԱՐԱՐՈՒԹՅՈՒՆՆԵՐԻ ԻՐԱԴՐԱՅԻՆ ՎԵՐԼՈՒԾՈՒԹՅՈՒՆ/EVENT-SEMANTICS ANALYSIS OF THE USA OFFICIAL ANNOUNCEMENTS ON 1915 EVENTS/ СОБЫТИЙНО-СЕМАНТИЧЕСКИЙ АНАЛИЗ ОФИЦИАЛЬНЫХ ЗАЯВЛЕНИЙ США О СОБЫТИЯХ 1915 ГОДА

Having the greatest power on nearly all states’ political standpoints the USA has touched upon the events of 1915 through myriad of political and official documents. The suppositional and subcontextual meaning of the USA political discourse and its semantical representation is initially studied in the scope of the theory of event semantics. The present article attempts to represent the events of 1915 in political discourse within the context of event analysis. The article examines the concept of complex event as an analytical tool, introducing a deep event modeling and event decomposition of causative verbs. Supposedly, the article intends to strucet the USA political discourse within the framework of official announcements and annual presidential statements.