Reviewerly/exHarmony huggingface dataset:
Intention to Use Mobile Banking Services: Extended Model

This research aims to evaluate the factors influencing the use of mobile banking by the customers. The extended model of this study was based on the technology acceptance model (TAM). Concerning this, the current research utilised two constructs of the TAM and integrated three new constructs into the model within mobile-banking context. The survey collected data from 205 mobile users who had their own experiences with mobile banking services provided by private banks in Jordan, these data were analysed using structural equation modelling (SEM). The results of this study demonstrated that perceived ease of use, perceived usefulness, perceived awareness, perceived bank credibility, and reference group influence had a positive impact on the use of mobile banking services by the customers. Banks should take these factors into account to promote positive perceptions of mobile banking to the customers.
Build a Desktop RetroPie Arcade

In previous chapters, we covered some significant milestones when building an arcade. On any arcade scale, we've talked about specific arcade hardware, methods of fixturing, and electronic component selection. Those methods will carry over to a larger scale. The larger scale also inherits some bonuses: as the cabinet expands in size, we gain some flexibility. A carger cabinet provides some much needed interior space. This build will have a bit more room regarding how to mount components and integrate electronics. If anything, this build doesn't involve working in cramped spaces. I will be covering build topics a bit more broadly if they've already been discussed in the previous chapter. Previously, we built a 1:8 scale arcade.
Language learning strategies employed by successful year 4 primary schools pupils in Shah Alam

Research on language learning strategies has been conducted in Malaysia as well. However, these studies did not include the language learning strategies employed by the successful primary school pupils in Shah Alam. The aim of the study is to identify language learning strategies employed by successful Year 4 primary school pupils in Shah Alam. A total of 30 Year 4 pupils who are 10 years old were chosen from a primary school located in the industrial area in Shah Alam, Selangor by using the purposive sampling method. Data was collected using a quantitative method approach. The instrument used in this study is a questionnaire with 35 items which is adapted from the Language Strategy Use Survey by Oxford and Chi, 2004 and also Gursoy, 2003. Collected data were analyzed using the descriptive approach. The findings portrayed that vocabulary enhancement strategy is employed mostly by the pupils compared to other learning strategies. The implication of this study may benefit ESL teachers, learners, and other researchers to enhance the effectiveness of English language teaching.
ANALISIS FAKTOR MOTIVASI YANG MEMPENGARUHI PRESTASI BELAJAR SISWA PADA BIDANG STUDI MATEMATIKA DI SEKOLAH MENENGAH PERTAMA NEGERI 1 NAMLEA

This study aims to determine the effect of motivation on mathematics learning achievement of students at Namlea 1 Middle School. This research is a form of research Ex Post Facto which is a research model that aims to examine the events that have occurred. The subjects in this study were all students of class VIIa of Middle School 1 Namlea, totaling 30 people. Data collection techniques using observation techniques, questionnaires and study documentation. Quantitative data analysis was carried out using statistical tests through three stages, namely the stage of data description, the prerequisite test phase of analysis and the stage of testing the hypothesis. Based on the results of the study note that the level of motivation and learning achievement of eighth grade students at Namlea Middle School 1 is categorized high. Associatively, the motivating factor has a positive and significant effect on mathematics learning achievement in class VIIa State Middle High School 1 Namlea.
A QoS ranking and controlling framework in virtualised clouds

In cloud computing, quality of service (QoS) has become an important issue either from the perspective of cloud providers or users. In this paper, we present a lightweight framework, namely cloud QoS ranking and controlling (CQRC), which integrates a QoS ranking service and a fine-grained QoS controller. The QoS ranking service provides an effective approach to quickly evaluating the QoS level of any cloud resources or services based on historical performances; the QoS controller is designed by using feedback control technique and is capable of self-tuning the underlying virtual machine (VM) configurations. The proposed framework is implemented and evaluated in a real-world cloud platform through a set of experiments and the results indicate that its QoS ranking service can significantly reduce the frequency of QoS violations and the QoS controller can achieve better tradeoffs between performance and cost for cloud providers.
중국인 학습자 대상 한국어 오류 연구 동향 분석

This paper analyzes prior research related to native Chinese speaking Korean Learners'' errors done from 2001 to the time of this writing. By looking at the prior research''s shortcomings and to provide suggestions for directions in which future research can delve into. Chapter 1 presents background research and need for this research. Chapter 2 details the theoretical background of error analysis and reviews the literature on error analysis trends. Separated into chronology of research, topic of research, research methods, and types of data, chapter3 examines the trends in the research of 666 research papers on native Chinese speaking Korean learners'' errors. Finally, chapter 4 proposes solutions for future studies on error research. This paper is significant in that it organizes statistically the prior research of the last twenty years, investigates the research categories/types, and provides baseline data to the error research literature. This paper should be helpful to future research regarding native Chinese speaking Korean learners. (Namseoul University)
Interfacing Genk: Citizen Participation and Critical Urban Intelligence

Urban interfaces are often understood as straightforward media to foster a standardized customer engagement of citizens with and in smart city processes. In contrast, in this essay we take Johanna Drucker’s humanities approach to interfaces as a starting point to redefine the urban interface as a critical zone of relations between multiple frameworks and embodied users. Our aim is to explore the merits of this approach in an urban development project around an old railway track in Genk (Belgium). Here, a low-tech urban interface—a leather carpet—was gradually developed as different people and institutions gave shape to their surroundings, and a more embedded and critical urban intelligence was realized in a process of democratic participatory design.
Implementasi Fuzzy Mamdani dalam Sistem Pendukung Keputusan Pemilihan Kamera DSLR bagi Pemula

Fuzzy logic is a method for mapping input to output. Fuzzy logic is used to support decision making. This method consists of three main processes, namely fuzzification, fuzzy inferential, and defuzzification. The results of this process depend on fuzzy compilation limits, fuzzy variables and non-fuzzy variables. The number of Digital Single Lens Reflex (DSLR) series that are developing at this time with diverse specifications makes it difficult for people to make a choice when buying a DSLR camera. Everyone has criteria that are considered according to their individual needs. In principle, the existence of SPK, only as a decision support system, not replace it. Including, making decisions in the selection of a product. The results of the implementation of the fuzzy method in the case of the selection of DSLR cameras tested in 10 data using Matlab are the highest value printed on the type of Canon EOS camera with the output output = 72.6 and the camera that is not recommended is located on the type of Canon EOS 700D camera with the output output = 17.1 .
Code-switching between informal Iraqi dialect and English language among Iraqi Arab speakers via WhatsApp application: linguistic and non-linguistic factors

Code-switching is described as the shifting that occurs between two or more languages concurrently within one conversation. This study aims to examine the application of code-switching between Informal Iraqi Dialect (IID) and English language among Iraqi Arab speakers of English via one of the smartphone applications, namely WhatsApp Messenger (WM). The study also seeks to recognize the types of code switching and motivations among Iraqi students of English for switching from IID into English language. This research adopted a qualitative approach, which involved Fifty (50) typed conversations of twenty (20) Iraqi post-graduate students studying at Universiti Putra Malaysia (UPM). Data were collected via two instruments, dubbed WM application to gather the typed conversations and semi-structured interviews. The results obtained from the WM application indicated that the most predominant type of code-switching (CS) used by the participants was intra-sentential CS, especially the intra-lexical code-switching. The findings suggest that the majority of the Iraqi students are inclined to code-switch to English language in smaller parts within the word boundary. The analysis of the interview data disclosed three motivations for the application of code-switching, namely linguistic, technological, and political factors.
Correlation verification of uncertainty sources for fan energy efficiency test based on Monte Carlo simulation

There are a large amount of input quantities and complicated correlation of uncertainty source which limit the reliability of the GUM method to evaluate the uncertainty of the measurement result in the fan energy efficiency test system. Based on the technical advantages of computer random sampling, Monte Carlo uncertainty evaluation method was given to solve the correlation of uncertainty sources of fan energy efficiency test system in traditional GUM method. It can be concluded through the experiment that the results of the GUM method without considering the correlation were basically consistent with the results of the MCM method obtained by computer sampling.
A multi-disciplinary approach for defining nickel and gold mineral systems; Halls Creek Orogen, Western Australia

SummaryGeodynamic models, geological-geophysical interpretations, and isotope analysis illustrate that there are links between the nickel and gold mineral systems in the Halls Creek Orogen, Western Australia. Whole-rock Nd and Ar-Ar analysis of rocks throughout the region, when compared with the geodynamic models suggest that nickel and gold mineralization in the Halls Creek Orogen can be related to basin development and subsequent basin closure during the convergence of North Australian Craton and Kimberley Craton, respectively. Whole-rock Nd analysis confirmed the input of juvenile melts in the centre of the orogen before the 1835-1805 Ma Halls Creek Orogeny, supporting the upwelling of decompression mantle melts during the basin development. These analyses also revealed the spatial links between nickel and gold mineralization and lithological units with positive εNd values. The results of geodynamic models, geophysical interpretation, and isotopic analysis are used to understand the critical processes in the gold and nickel mineralization, which are presented by predictor maps. The GIS-based knowledge-driven fuzzy method used to integrate the predictor maps and create the prospectivity maps. Herein we show that mafic-ultramafic units prospective for nickel mineralization formed by upwelling of decompression mantle melt during crustal thinning and extension during basin development, and typically consist of the most juvenile magmas in the region. Whereas, gold deposits formed during the compressional regime and basin closure, and are located along a major shear zone separating two terranes. Another critical element that appears to be related to gold prospectivity is the presence of lithologies with a juvenile signature. In contrast to nickel analyses which are closely related to mafic-ultramafic units, the source component seems less influential when attempting to target orogenic gold deposits.
Camera and LiDAR Fusion for On-road Vehicle Tracking with Reinforcement Learning.

We formulate camera and LiDAR fusion tracking as a sequential decision-making process. With our deep reinforcement learning framework, we try to optimize the tracking trajectory to be as accurate, smooth, and long as possible. In contrast to traditional fusion algorithms involving complex feature and strategy design and hyperparameters tuned for different scenarios, our fusion agent can learn the confidence of each input by tracking the results from raw observation in a data-driven fashion. Given the input states of different sensors, our approach chooses one input with a higher expected cumulative reward as the observation of a Kalman filter to iteratively predict the target position. The expected cumulative reward is estimated with a convolutional neural network, trained with a modified DQN algorithm, which takes inputs from both LiDAR and a camera. Through case studies and quantitative result evaluation on our dataset from the 4th Ring Road in Beijing, our algorithm is validated to achieve more accurate and robust tracking performance.
An improved clinical data similarity algorithm based on ICD10

Abstract Disease prediction helps prevent disease and early diagnosis, and accurate classification of patients greatly improves the accuracy of disease prediction. Today’s massive multi-dimensional medical data and its similarity algorithms provide the basis for the classification of clinical diseases. Based on this, we randomly generated the simulated clinical data of ICD10 structure, used the improved similarity algorithm to calculate the similarity and classification of the two patients, and found the patients belonging to different disease categories in the classified patient group. This finding provides a scientific basis for the correction of genetic algorithms and genetic research.
Pengaruh Model Pembelajaran Kooperatif Tipe STAD Dan Kecerdasan Interpersonal Terhadap Hasil Belajar Pendidikan Kewarganegaraan Siswa Kelas X SMA Negeri 3 Pandeglang

The purposes of this research is to determine:(1) The difference between  students’ learning achievement of civics education between students who learn by using cooperative learning STAD model and using expository method (lecture); (2) the difference between  students’ learning achievement of civics education between students who have high interpersonal intelligence and students who have low interpersonal intelligence; (3) the interaction of applying cooperative learning STAD model and interpersonal intelligence toward civics learning achievement; (4) the difference students’ learning  achievement of civics education between the students using cooperative learning STAD  model who have high interpersonal intelligence and the students using expository learning method who have high interpersonal intelligence; and (5) the difference learning achievement of civics education between the students using cooperative learning STAD model who have low interpersonal intelligence and the students using expository learning method who have low interpersonal intelligence.This research uses quantitative approach with experimental method. The results show (1) students’ civics education achievement by applying cooperative STAD learning model is higher than students’ civics education achievement by expository learning method; (2) students’ civics education achievement who has high interpersonal intelligence is higher than students’ civics education achievement who has low interpersonal intelligence; (3) there is interaction between applying cooperative STAD learning model and high interpersonal intelligence towards students’ civics education achievement; (4) students’ civics education achievement who has high interpersonal intelligence by applying cooperative STAD learning model is higher than the students’ civics education achievement who has high interpersonal intelligence by applying expository learning method; and (5) students’ civics education achievement who has low interpersonal intelligence by applying cooperative STAD learning model is higher than the students’ civics education achievement who has low interpersonal intelligence by applying expository learning method.
An Overview of Sentiment Analysis: Concept, Techniques, and Challenges

"Data is the new oil," a statement given by UK based mathematician, Clive Humby very accurately suits the current scenario of the World Wide Web. The unimaginable usage of online opinion sharing platforms is resulting in the generation of a large volume of opinion-rich data. This opinion rich data can be in the form of reviews given by people regarding any product, brand, service or something related to their experience and emotion about any topic. This data can be used by organizations to know what their customers really think, want, and need. Sentiment analysis is one of the technologies working behind this analysis. It is the process of mining text to extract subject information which can help organizations understand the social sentiments behind their product or service. This paper focuses on the aspects related to sentiment analysis. Various techniques that can be applied to sentiment analysis are discussed in this paper. This paper also focuses on how sentiment polarity of the data can be obtained using various sentiment classification techniques. Various applications and challenges related to sentiment analysis will also be explained in this paper.
Frames Selection Based On Modified Entropy And Object Motion In Video Steganography

Steganography schemes have been widely implemented in multimedia communication. Multimedia data, such as videos are often compressed to reduce the storage in the limited bandwidth. However, most video steganography schemes are not resistant to compression. The video provides additional hidden space in the image frame sequences. This research proposes a frame selection technique based on object motion and modified entropy in video steganography. The object motions in the video frame are determined by horizontal and vertical of motion vectors. The video frames that have object motion are computed by using modified entropy. The lowest modified entropy frames are selected for concealing a secret message. The proposed frame selections able to produce minimum distortion of stego-video compare to non-frame selection. The experimental results show that our scheme achieves good robustness of message recovery in terms of Bit Error Rate (BER) and Normalized Cross-Correlation (NC). The recovered messages of the proposed steganography scheme can survive under video compression. Â© 2019, International Journal of Scientific and Technology Research. All rights reserved.
Integration of the lesson and extracurriculum activities as the means of developing the cognitive activity of a younger schoolchild

Today, in the Russian system of comprehensive education, extracurricular activities are widely involved along with traditional training sessions in order to achieve qualitatively new learning outcomes. In the proposed work, the authors consider how after-hours pupils learn to organise their activities, independently acquire knowledge, master the forms of productive learning, that is, they accumulate their experience of "learning skills" – cognitive, regulatory, and communicative universal learning activities necessary to continue their studies. The novelty of the article consists in the fact that the described experience preserves the unity of the educational systems "lesson" – "extracurricular activities". Using theexample of an optimisation model, the authors show the development of the cognitive activity of younger schoolchildren. What is the most intelligent, is the general intellectual direction of extracurricular activities, in which this quality of personality is formed quite fully and systematically.
Learning Semantic Correspondences from Noisy Data-text Pairs by Local-to-Global Alignments

Learning semantic correspondences between structured input data (e.g., slot-value pairs) and associated texts is a core problem for many downstream NLP applications, e.g., data-to-text generation.Large-scale datasets recently proposed for generation contain loosely corresponding data text pairs, where part of spans in text cannot be aligned to its incomplete paired input.To learn semantic correspondences from such datasets, we propose a two-stage local-to-global alignment (L2GA) framework.First, a local model based on multi-instance learning is applied to build alignments for texts spans that can be directly grounded to its paired structured input.Then, a novel global model built upon a memory-guided conditional random field (CRF) layer aims to infer missing alignments for text spans not supported by paired incomplete inputs, where the memory is designed to leverage alignment clues provided by the local model to strengthen the global model.In this way, the local model and global model can work jointly to learn semantic correspondences in the same framework.Experimental results show that our proposed method can be generalized to both restaurant and computer domains and improve the alignment accuracy.
Real-time Vision-based Autonomous Navigation of MAV in Dynamic Environments

Safe navigation in unknown environments is a challenging task for autonomous Micro Aerial Vehicle (MAV) systems. Previous works generally avoid obstacles by assuming that the environment is static. The purpose of this thesis work is to develop a MAV system that can navigate autonomously and safely in dynamic environments. We present an onboard vision-based approach for the avoidance of moving obstacles in dynamic environments. This approach uses a state-of-art visual odometry algorithm to estimate the pose of MAV and an efficient obstacle sensing method based on stereo image pairs to estimate the center position, velocity, and size of the obstacles. Considering the uncertainties of the estimations, a chance-constrained Model Predictive Controller (MPC) is applied to achieve robust collision avoidance. The method takes into account the MAV’s dynamics, state estimation and the obstacle sensing results ensuring that the collision probability between the MAV and each obstacle is below a specified threshold. The proposed approach is implemented on a designed experimental platform that consists of a quadrotor, a depth camera, and a single-board computer, and is successfully tested in a variety of environments, showing effective online collision avoidance of moving obstacles.