Reviewerly/exHarmony huggingface dataset:
과정 중심 말하기 수행평가가 고등학생 영어 학습에 미치는 효과

This study is to apply a process-oriented speaking performance assessment into high school English classes and to verify the impact of the performance assessment on students’ affective domain of English learning and English language proficiency. Based on the 2015-revised national curriculum, process-oriented speaking performance assessments are conducted for six periods of English classes for one hundred second year students in J high school in Chungbuk province. Findings are: process-oriented speaking performance tests cause students to improve their language proficiency and accuracy on segmental and suprasegmental, semantic group clustering via constant feedbacks from teacher and peers, and in turn the feedbacks contributes to students’ enhancement of their speaking performance. They also help improve students’ affective attitudes toward English learning by being more aware of the self-learning processes, more involved and in charge of their own learning and alleviates the psychological burden of work by working together in small groups.
Analysis of Different Type of Techniques Through Machine Learning

Machine learning framework adequately realizes how to evaluate from preparing set of finished undertakings. The principle objective and commitment of the survey is to help the exploration on master estimation, i.e. to ease other analyses for significant master estimation thinks about utilizing machine-learning methods. This paper shows the most utilized machine learning methods, for example, neural systems, case based thinking, grouping and relapse trees, govern enlistment, hereditary calculation and hereditary programming for master estimation in the field of programming advancement. Our audit of concentrate not just recommends that these strategies are aggressive with customary estimators on one informational index, yet additionally delineate that these techniques are delicate to the information on which they are prepared. This paper gives a broad survey of concentrates identi fied with master estimation of programming improvement utilizing Machine-Learning Techniques (MLT).
Beamer, Benz, or Bentley: Mentions of products in hip hop and R&B music

Mentions of commercial products are common in hip hop and R&B lyrics, relative to other genres of popular music, although the potential impacts of this are not wellunderstood. Since these songs reach millions of people daily, it is pertinent to study the nature of these product mentions – in turn facilitating further research on their effects. In order to provide an overview of the product mentions that are present in hip hop and R&B lyrics between 1990 and 2017, we undertook a large-scale content analysis (N = 2,650 song lyrics). Mentions of products were frequent, and the types of products being mentioned remained mostly consistent (predominantly cars, fashion and alcohol), although the rate increased dramatically over time. Most mentions were of high-end brands and were framed neutrally. Overall, lyrics mentioning products contained more diverse vocabulary and were much more likely to mention money. These findings are interpreted in relation to prior research and the music business in general.
특수기 소포우편 물동량 예측시스템 개발

In the postal logistics service, rapid change in mail volume and requirements for shortening delivery time make operational optimization a fundamental concern. The mail traffic forecasting is essential for optimizing the resource operation of major postal infrastructures such as post offices, sorting centers, exchange centers, and delivery stations. In particular, in extreme event periods where the volume of traffic increases by about 1.4 times compared to normal, it is important to establish a resource operation plan at the logistics infrastructures for ensuring delivery service quality to the public. This paper addresses an extreme event prediction problem for Korea Post''s parcel logistics service. The main purpose of this paper is to describe the development of extreme event prediction system and to introduce an application of the prediction system to postal parcel service site. The extreme event prediction system for Korea Post''s parcel logistics service develops a hybrid prediction model based on internal and external factor-based features and ensemble models, and enables flexible prediction in consideration of traffic patterns by applying input features and model selection and parameter adjustment functions.
Blockchain-based secure communication in smart cities

The smart city aims for analyzing big data collected from massive Internet of Things (IoT) devices deployed across the city, to get an understanding of connected society, and improve the services provided to the citizens. The rapid development of 5G and beyond communication technologies, IoT, cloud computing, mobile edge computing, and interconnected networks has led to a new digital urban environment (i.e., smart city). Despite several potential benefits, the smart city environment has a major challenge of information security and privacy. A comprehensive analysis of architecture and key elements of smart city along with security and privacy requirements is provided in this chapter. We argue that distributed ledger technology (blockchain) can be used for secure communication in the smart city. Blockchain-based security mechanisms applied to different aspects of the smart city are discussed in detail. Some case studies are presented for smart cities where blockchain has been applied. We also highlight some open issues and future research directions for blockchain-based smart city environments.
A Call for Deep learning in Healthcare

The concept of personalising patient care has a long history, and current advancements in diagnostic medical imaging and molecular medicine are slowly but steadily revolutionising healthcare services by providing information and diagnostic tools that allow for tailored patient treatment. Multiple heterogeneous elements, such as socio-demographics, gene variability, environmental, and lifestyle factors, must be considered in order to facilitate personalized/precision treatment. As a result, one of the most pressing difficulties in personalised medicine is transforming enormous amounts of multimodal data into decision support tools capable of bridging the gap between research and clinical practise.Deep learning (DL) provides a unique answer to these issues, allowing for the acquisition or building of high-accuracy, multi-modal prediction models that will soon enable the realisation of the personalised medicine vision.
EFFICIENT TOUR PLANNING FOR A MEASUREMENT VEHICLE BY COMBINING NEXT BEST VIEW AND TRAVELING SALESMAN

Abstract. Path planning for a measuring vehicle requires solving two popular problems from computer science, namely the search for the optimal tour and the search for the optimal viewpoint. Combining both problems results in a new variation of the Traveling Salesman Problem, which we refer to as the Explorational Traveling Salesman Problem. The solution to this problem is the optimal tour with a minimum of observations. In this paper, we formulate the basic problem, discuss it in context of the existing literature and present an iterative solution algorithm. We demonstrate how the method can be applied directly to LiDAR data using an occupancy grid. The ability of our algorithm to generate suitably efficient tours is verified based on two synthetic benchmark datasets, utilizing a ground truth determined by an exhaustive search.
Decorative Drawings in Rhythmically Organized Drawings, as a Form of Building Motor Skills and Feelings of Coherence in Preschool Children

When creating decorative drawings, preschool children build stylized forms – elements and ornaments, rhythmically connected in decorative compositions. The use of rhythm as the main mean of expression is the basis for the improvement of controlled motor skills, which are a necessary condition for the construction of written speech. Developing a sense of coherence between the individual elements and connecting them into a single whole is the challenge in building a decorative composition. The use of an exact number of decorative elements and their logical and rhythmic alternation in the composition help to build a sense of coherence and perfection in the decorative drawings of preschool children.
Towards Designing a Method to Create Sticky Information Security Training for SMEs: Identifying Design Factors

The risk of being impacted by a cyberattack is high, because of more professional attacks. Thereby, cyber criminals are bypassing technological countermeasures through tricking users. Recently collected data during the SARS-CoV-2 pandemic demonstrate, that cyberattacks including social engineering are among the main threats, especially for Small and Medium-sized Enterprises (SME). (Information) Security Education and Training Awareness (SETA) is proposed to be an effective countermeasure. However, the effects of SETA fade rapidly over time and learnings are not applied in practice sustainably. Thus, we state that a method is required to create SETA programs with sustainable learning outcomes for SME. To develop such a method, we follow the Design Science Research Methodology and share insights of our first design cycle in this article. We conducted a literature review and analyzed factors of failure and success regarding the design of sustainable SETA programs. Furthermore, we sketch our plans for design cycle 2.
3D Modelling of the Northern Upper Rhine Graben Crystalline Basement by Joint Inversion of Gravity and Magnetic Data

&amp;lt;p&amp;gt;The crystalline basement of the Upper Rhine Graben presents an attractive target for deep geothermal projects due to its favourable temperatures and its high potential as a fractured and faulted reservoir system. It is already exploited at several sites, e.g. Soultz-sous-For&amp;amp;#234;ts or Landau, and further projects are currently planned or under development. The crystalline units are furthermore the main source of radiogenic heat production and thus, together with the shallow Moho depth and convective heat transport along large fault zones, significantly contributing to the crustal temperature field. For these reasons, we developed the most detailed 3D geological model of the basement in the northern Upper Rhine Graben to date within the Interreg NWE DGE-ROLLOUT and Hesse 3D 2.0 projects. Due to the small number of very deep boreholes as well as seismic profiles reaching the basement beneath the locally more than 5 km thick sedimentary cover, we additionally used high-resolution magnetic and gravity datasets. In contrast to common deterministic modelling approaches, we performed a stochastic joint inversion of the geophysical data by applying a Monte Carlo Markov Chain algorithm. This method generates a large set of random but valid models, which enables a statistical evaluation of the results, e.g. concerning the model uncertainties. For a realistic attribution of the model, we used existing petrophysical databases of the region and measured the magnetic susceptibility of more than 430 rock samples. As a result of the inversion, high-resolution voxel models of the density and susceptibility distribution were generated, allowing conclusions about the composition and structure of the crystalline crust, which leads to a reduction of uncertainties and risks associated with deep geothermal drillings in the northern Upper Rhine Graben. Furthermore, our model will serve as a basis for realistic simulations of heat transport processes in the fractured basement and a meaningful assessment of the deep geothermal potential in the future.&amp;lt;/p&amp;gt;
Understanding mathematics: Some key factors

Mathematics is well known as a subject area where there can be problems in terms of understanding as well as retaining positive attitudes. In a large study involving 813 school students (ages approximately 10-12) drawn from two different school systems in Pakistan, the effect of limited working memory capacity on performance in mathematics was explored along with a survey of areas of difficulty and student attitudes. This involved looking at student perceptions of their experiences, the nature of the difficulties they have with mathematics and possible reasons for these difficulties. The overall aim is to explore the extent of the effect of working memory and to gain insights so that practical ways forward to enhance mathematics education can be identified. It was found that limited working memory capacity has a very strong influence on performance, confirming other studies. Indeed, if the cognitive load exceeds the capacity of working memory, understanding becomes a casualty, with consequent attitude deterioration. Students need to be able to see that mathematics has a purpose in being able to be applied to real-life situations. However, attempts to develop applications may often generate further working memory overload. Curricula devised by those outside the classroom can sometimes be inappropriate while topics causing the greatest problems at these ages and include areas of geometry, statistics and the applications of mathematics.
MINERAL CHEMISTRY OF FELDSPAR AND AMPHIBOLE APPLICATION OF DIFFERENT GEOTHERMOBAROMETRY METHODS AND OXYGEN FUGACITY, DETERMINATION OF MAGMATIC SERIES, ORIGIN AND TECTONOMAGMATIC CLASSIFICATION OF SHIRKUH GRANITOID BATHOLITH, YAZD, IRAN

Batholith of Shirkuh, Yazd, is part of the central Iranian structural zone, located southwest of the province. The lithology of this complex comprises mostly monzogranite and granodiorite and some quartz monzonite, quartz monzodiorite and syenogranite.Plagioclase, quartz, orthoclase, biotite and amphibole are the dominant minerals in these rocks. The composition of plagioclases varies from labradorite to oligoclase, and alkali feldspars belong to the orthoclase category. Amphiboles are calcic, rich in iron and Fe-Mg-Mn amphiboles, and range from ferro-hornblende to tschermakite, and tschermakite hornblende. According to various geobarometry methods using the amphibole composition, it is estimated that the calc-alkaline batholith has been formed in a supra-subduction tectonomagmatic environment at 700–900 °C and 0.8–1.5 kbar pressure under high oxygen fugacity. Moreover, based on the thermometry results of feldspars, the emplacement temperature was obtained in the 770–920 °C range by the Anderson method for the Shirkuh granitoid batholith
Advanced Mechanism to Achieve QoS and Profit Maximization of Brokers in Cloud Computing

Cloud computing is a widely used technology today and thus, large number of applications are being stored in the cloud.To cater to the needs of the consumers an intermediate role known as cloud broker has been introduced.It helps to cut down overall expenses of the cloud users.The proposed system concentrates on configuration of the cloud broker to improve profit.This maximization scheme depends upon various factors like customer request, selling price of the resource, purchasing price of the resource, intensity of the request and so on.The system developed, aims at maximizing the profit of the cloud broker who services consumer requirements by providing cloud infrastructure at a lower cost from an infrastructure vendor.Availing payas-you-go schemes or on-demand payment has proven to be useful.The complex cloud landscape along with various billing schemes paves a way for a profit maximization model that incorporates temporal multiplexing by a middleman entity for a better economic upfront.The resource multiplexing is further enhanced by incorporating M/D/c queueing model and short-term and long-term renting schemes to optimize the resource allocation.The entire application has been implemented using Java especially the NetBeans IDE 8.2.Different algorithms were compared to further enhance the pricing scheme selection.Finally, Hill-Climbing algorithm is used to allocate the resources dynamically.The system further notifies the cloud broker on resource shortage through dynamic disk utilization graph.The proposed system considers quality of service and price of service as the determining factors in maximizing the net profit of the cloud broker.
Using Dapr in ASP.NET Core

In this chapter, you will learn about the integration between Dapr and ASP.NET Core. If you made it so far in the book, you have already seen a lot of examples implemented in ASP.NET. Dapr does not need really anything special to be used with any web framework. However, when it comes to ASP.NET Core, Dapr has some syntactic sugar that makes it even easier. There is support for using the State Management and the Publish and Subscribe building blocks natively inside a controller. There is also a way to expose a secret store as an ASP.NET Core configuration. Furthermore, implementing a gRPC service doesn’t mean that you have to import the Protobuf files of Dapr in order to call its gRPC API. It comes pre-packaged inside the support for ASP.NET Core.
Textual Analysis of Indian English Newspapers (A Corpus Based Study)

AbstractThe study was largely conducted content analysis of websites covering the widely claimed most popular online newspapers; Times of India (TOI), Hindustan Times (HT) and The Hindu (TH).Very few research studies have been conducted on textual analysis of news content of Indian newspapers. The study was borrowed from amplification effect of media of (Watson, 1998) that says “by giving intensive coverage to certain stories and issues, their importance is amplified”.The objectives determined for the study were interpreted and analyzed with Antconc statistical tools to get accurate answers. It is discovered that content of the story published by the different newspapers unambiguously reflect or at least indicate their agenda and perception. This study finds this quality in line with general understanding of press being the responsible body of society and also the fourth pillar of democracy. This study examines the effective agenda setting role of the Indian online newspapers, keeping in background the emotions of their readers. In a bid to develop empirical result, while scrutinizing the news stories, it focuses on the classiﬁcation of different categories of news in terms of political, social ,economic etc polarity. This is primarily to explore and establish the connection between content and rnewspapers. In order to identify and substantiate the study, a total of 8,640 news stories spanning over a decade from 2006 to 2016 were evaluated. Considering the huge quantum of data, it was realized that automatic system must be resorted to put them in orderly fashion. Lastly, we elaborate on the different approaches for the machine treatment of subjective communication (opinion mining) and present our findings while bringing out their implications.
LEO: Liquid Exploration Online

This article introduces a novel approach to the online complete- coverage path planning (CCPP) problem that is specically tailored to the needs of skid-steer tracked robots. In contrast to most of the current state-of-the-art algorithms for this task, the proposed algorithm reduces the number of turning maneuvers, which are responsible for a large part of the robot's energy consumption. Nevertheless, the approach still keeps the total distance traveled at a competitive level. The algorithm operates on a grid-based environment representation and uses a 3x3 prioritization matrix for local navigation decisions. This matrix prioritizes cardinal di- rections leading to a preference for straight motions. In case no progress can be achieved based on a local decision, global path planning is used to choose a path to the closest known unvisited cell, thereby guaranteeing completeness of the approach. In an extensive evaluation using simulation experiments, we show that the new algorithm indeed generates competi- tively short paths with largely reduced turning costs, compared to other state-of-the-art CCPP algorithms. We also illustrate its performance on a real robot.
Kenworth T800 In Traffic [1.36] A UP

This mod adds Kenworth T800 traffic Standalone Compatible with other traffic mods and traffic packs Work in 1.35 1.37 Authors: GT-Mike (Wolfi), is ...
Image Processing for Facial Expression Recognition

Human facial expressions give a lots of information’s without communication. Itshould help in so many areas for virtually rather than articulately. Facial expressionrecognition important for recognizing for criminal, unhealthy people’s mentality,watching anything in television for that expressions and so on. Facial recognitiondetect expression using some tools and techniques which will be easy and best way todetect some expression. In this facial expression detection directly detect the expressions ofhuman only using webcam that can be very useful for identify the expression of manyother areas.some process used in the image processing for detecting human expressionusing live image and video as an input. Detecting expression which follow fourpowerful steps which is very important for every image processing. first step shouldgive the clarity of image if it is live image also it will clear image which is very easy,second step is to registration of image which will crop image and capture image, thirdstep which gives scaling, contrast to image and last step which give emotions nameafter recognizing all others step.Some steps should follow to recognize the expression. Its input should be humanshould seat in front of webcam which come after run the code written in python andafter execution of code one camera will be open and then it will detect expression asper the movement of facial movement and also video which is store in file both inputshould be carried out for recognizing the expressions after this input, outcome shouldcome in the format of text which is different emotions name. The output of thisproject of identify emotions of human should include input as an image format, itshould be image which is capture by camera which is store in file and output shouldbe in text format between seven different universal expression.
Hubungan Efikasi Diri Terhadap Prestasi Belajar IPS Siswa Sekolah Dasar

The main problem that is considered in this study, is the quality of education is not determined by a single factor, namely student learning outcomes which are a reflection of learning effort, the better the learning effort, the better the results achieved. Good learning outcomes will be achieved if they can overcome the learning difficulties they experience, but there are a number of variables that influence each other. This type of research is ex-post facto causality. The population in this study were elementary students of Mitra PGSD Bone. Data were collected through 54 selected samples using cluster random sampling techniques. This study aims to: (1) To find a picture of self-efficacy, (2) To find out and explain the relationship of self-efficacy to students' social studies learning achievement. Data were analyzed with descriptive statistics and inferential statistical analysis. The results showed that: (1) Most elementary students had: self-efficacy in the medium category, and social studies learning outcomes in the moderate category; (2) Self-efficacy has a significant relationship with students' social studies learning achievement. Conclusions, if students' self-efficacy continues to be improved will have an impact on learning outcomes that are even better and can make adjustments in the learning process.