Reviewerly/exHarmony huggingface dataset:
한국어 학습자의 모어 간섭에 의한 오류에 대하여-우즈베키스탄 학습자의 말하기에 나타난 조사 사용을 중심으로-

The purpose of this study is to investigate the patterns of postposition errors in the speech of Uzbekistani Korean learners at the intermediate level and examine their causes. The analysis results of errors in frequency and type show that postposition errors due to the interference of mother tongue were the most. The causes of postposition errors among Korean learners whose mother tongue was the Uzbek language were examined according to errors due to the interference of mother tongue and use of target language. Errors due to the interference of mother tongue were further divided into preclusive interference errors and intrusive interference errors and contrasted with the Uzbek language to sort out the characteristics of errors. The findings raise a need to explain differences between Korean and Uzbek languages in the education of Korean postpositions to reduce postposition errors due to the interference of mother tongue among Uzbekistani Korean learners. (Sunchon University)
Evaluating Strategies for Selecting Test Datasets in Recommender Systems

Recommender systems based on collaborative filtering are widely used to predict users' behaviour in large databases, where users rate items. The prediction model is built from a training dataset according to matrix factorization method and validated using a test dataset in order to measure the prediction error. Random selection is the most simple and instinctive way to build test datasets. Nevertheless, we could think about other deterministic methods to select test ratings uniformly along the database, in order to obtain a balanced contribution from all the users and items. In this paper, we perform several experiments of validating recommender systems using random and deterministic strategies to select test datasets. We considered a zigzag deterministic strategy that selects ratings uniformly across the rows and columns of the ratings matrix, following a diagonal path. After analysing the statistical results, we conclude that there are no particular advantages in considering the deterministic strategy.
Frequent Itemset Generation for Analyzing Customer Buying Nature using Bit Vector Mining

The paper introduces an efficient algorithm using bit vector to find frequent itemsets from a huge set of itemsets. The existing frequent itemset generation algorithms lack efficiency in terms of time and space. As a result, the need for new frequent itemset mining algorithms that could tackle the new trends are required. Here, the purchased items in a transaction are represented in terms of bit vectors. A bit vector is a vector in which each element is represented in terms of bits (so its value is either 0 or 1). The database is scanned only once. The k-frequent itemsets are obtained by performing LOGICAL AND operation between the items in the scanned table. By doing so, the time and space consumed in determining the frequent itemsets is reduced.
Platform for Integrating and Testing Tools which Transform Natural Language Queries into SPARQL Queries

In the paper we discuss how to support the process of creating tools which transform natural language (NL) queries into SPARQL queries (hereinafter referred to as a transformation tool). In the introduction, we describe the relevance of the task of understanding natural language queries by information systems, as well as the advantages of using ontologies as a means of representing knowledge for solving this problem. This ontology-based data access approach can be also used in systems which provide natural language interface to databases. Based on the analysis of problems related to the integration and testing of existing transformation tools, as well as to support the creation and testing own transformation modules, the concept of a software platform that simplifies these tasks is proposed. The platform architecture satisfies the requirements for ease of connecting third party transformation tools, reusing individual modules, as well as integrating the resulting transformation tools into other systems, including testing systems. The building blocks of the created transformation systems are the individual transformation modules packaged in Docker containers. Program access to each module is carried out using gRPC. Modules loaded into the platform can be built into the transformation pipeline automatically or manually using the built-in third party SciVi data flow diagram editor. Compatibility of individual modules is controlled by automatic analysis of application programming interfaces. The resulting pipeline is combined according to specified data flow into a single multi-container application that can be integrated into other systems, as well as tested on extendable test suites. The expected and actual results of the query transformation are available for viewing in graphical form in the visualization tool developed earlier.
An Approach Implementing Mobile Application for Herbal Treatment

A fully automated method for the recognition of medicinal plants using computer vision and machine learning techniques has been presented. Leaves from 24 different medicinal plant species were collected and photographed using a smart phone in a laboratory setting. A large number of features were extracted from each leaf such as its length, width, perimeter, and area, number of vertices, colour, perimeter and area of hull. Several derived features were then computed from these attributes. The best results were obtained from a SVM classifier using a 10-fold cross-validation technique. With an accuracy of 90.1%, SVM classifier performed better than other machine learning approaches such as the k-nearest neighbour, NaïveBayes, KNN and neural networks.This is implemented using Android studio software and we obtained a working module.
Real-time Motion Detection with High-speed Vision and Local Parallel Processing

In order to achieve highly real-time performance for motion detection and control system, a vision system based on high-speed CMOS sensor and local FPGA processing was designed. In this system, the data of high-speed CMOS sensor were directly collected by a near-end FPGA, on which the image sequences are processed by the logic of pipeline structure and a fast method called projection average algorithm was applied for centroid detection. With the synchronous processing and parallel computing, highly real-time target recognition and centroid detection were realized. Experiments show that this system realizes real-time detection of 1146fps at 560×480 resolution, whose target positioning accuracy is 1 pixel and detection latency is only 593 clock cycles, about 6.59 us at 90 Mhz. This high-speed vision-based object detection system achieves highly real-time performance and can be applied to a variety of high-speed motion measurement and real-time control systems.
An Intelligent Testing Strategy for Vocabulary Assessment of Chinese Second Language Learners

Testing is an important tool to monitor learning effects.However, it usually costs a large amount of time and human labor to build an item bank and to test large number of students.In this paper, we propose a novel testing strategy by combining automatic item generation (AIG) and computerized adaptive testing (CAT) in vocabulary assessment for Chinese L2 learners.Firstly, we generate three types of vocabulary questions by modeling both the vocabulary knowledge and learners' writing error data.After evaluation and calibration, we construct a balanced item pool with automatically generated items, and implement a three-parameter computerized adaptive test.We conduct manual item evaluation and online student tests in the experiments.The results show that the combination of AIG and CAT can construct test items efficiently and reduce test cost significantly.Also, the test result of CAT can provide valuable feedback to AIG algorithms.
Identifying and Prioritizing the Barriers of Implementation of Knowledge Management in Industrial Units and Providing Solutions to Eliminate them (Case Study: ParsianFanavaran Group)

One cannot ignore the importance of knowledge in today's complex and global environment.Organizations that know how to collect, distribute and manage information effectively become industry leaders.Organizations are increasingly facing global competition and more complex customers.To survive in the competitive world, they should have an innovation in reducing the costs and expanding the market and increasing the efficiency of their processes.The importance of knowledge management is revealed at this point.Knowledge management (KM) not only has been proposed for the cost effectiveness and management effectiveness in problem solving, decision making and innovation, and other elements are needed to maintain and develop competitive advantage, but also it has been proposed more for obtaining, classifying, maintaining, and disseminating, and listing the knowledge and expertise consisting of an organizational memory in unstructured manner in the organization.Today's increasingly complex and changing competitive environment demands organizations that can survive in this area and make an effort to implement KM in order to gain competitive advantage.As the probability of failure of KM projects is high, these organizations should be able to predict their conditions with predictable scientific methods and strategies and implement appropriate strategies for the implementation of the project to achieve success.Considering these conditions, the project of the implementation of knowledge management in their organizations is facing challenges and complexities, so that lack of identifying and eliminating these barriers before and during its implementation will lead to a failure of the KM project.Accordingly, despite the resources and time spent in the organization, it will be impossible to use the benefits of implementation of knowledge management project.In this study, the status of the studied organization was firstly investigated in terms of implementation of knowledge management.Then, the main barriers of implementation of knowledge management were identified through library resources, interviews and questionnaires.After that, the priority and importance of barriers were identified and the relationships among the data were analyzed.Having a proper and realistic view and perspective and considering the current status of the organization, some recommendations were presented to eliminate these barriers of order to increase the probability of success of the implementation of knowledge management project.
CHILD FACE RECOGNITION SYSTEM USING MOBILEFACENET

Face recognition is a kind of identifying people in image. It matches the database of known faces and input image of unknown face. Deep learning is one of the state-of-art technologies which achieve state-of-art performance on face recognition. In this paper, we develop child face recognition using MobileFaceNet. MobileFaceNet is efficient Convolutional Neural Network (CNN) models and it uses more than 1 million parameters. MobileFaceNet is used for feature extractions. Since MobileFaceNet is one of the types of light weights models, we can apply this face recognition system on mobile and embedded devices. Dlib is used for preprocessing and K-Nearest Neighbors (KNN) is used for classification process. MobileFaceNet is trained by ArcFace loss and it achieve the 99% accuracy on child face dataset.
Salient Object Detection via Deep Hierarchical Context Aggregation and Multi-Layer Supervision

The aggregation of hierarchical information is vital for saliency detection. To achieve this, most existing saliency detectors apply various network structures to fuse features. But most of them utilize shallow skip connections and only concentrate on the final results, which can not guarantee the model to learn the rich and accurate contextual information. To address these problems, we propose a network with deep layer aggregation and multi-layer intermediate supervision. We utilize deep layer aggregation to fuse features iteratively and hierarchically across layers to obtain richer information. Then we add multi-layer intermediate supervision on each side-output layer to capture more accurate contextual information. We evaluate our method on six benchmark datasets under various metrics and it achieves the new state-of-the-art.
AN ANALYSIS OF RELATIVE CLAUSES MADE BY THE EIGHT GRADE STUDENTS OF SMP NEGERI 3 SELAT IN ACADEMIC YEAR 2017/2018

The present study is dealt with An Analysis of Relative Clauses Made by the Eight Grade Students of SMP Negeri 3 Selat in Academic Year 2017/2018. The researcher was interested in making an analysis of Relative clauses made by the students under study. The present study is intended to assess the acquisition of relative clauses made by the eighth-grade students of SMP N 3 Selat Karangasem in academic year 2017/2018. In other words, this study is to figure out the ability of the subject under study in understanding relative clauses. The present’s study which use ex-post facto research design with descriptive analysis was intended to answer the following research question: to what extent is the acquisition of relative clauses made by the eighth-grade students of SMP N 3 Selat Karangasem in academic year 2017/2019? In order to answer the research question before, the data were required for the present study which in the form of raw score is showing the ability of the students in mastering relative clauses, were collected by administering the valid and reliable research instrument in form of multiple-choice test items. Then the data is analyzed by using Norm-Reference measure with five standard values. The populations of the present study are the eighth-grade students of SMP Negeri 3 Selat which consist of 206 students. They are considered to have heterogeneous characteristics. In this study 30 students are considered as a sample of the study by using random sampling technique. The data of the study is clearly showed that: (1) there are 4 students or (13.33%) out of 30 students under study who showed excellent ability of relative clauses. (2) There are 4 students or (13.33%) out of 30 students under study who showed good ability of relative clauses (3) there are 10 students or (33.33%) out of 30 students under study who showed sufficient ability of relative clauses. (4) There are 12 students or (40%) under 30 students under study who showed insufficient ability of relative clause. (5) No one students or (0%) out of 30 students who showed poor ability of relative clauses. In the result of the study were used as the basses to assign level/grade to the subject under study, there are 12 students or 40% out of 30 students under investigation who fail in learning and acquiring relative clauses. It means that 40% of them still have low ability. The finding of the present study can be used as the basses in planning much better language teaching especially in mastering grammar or relative clauses.
Google Drive: A Boon for Developing a Web-based Collaborating Working Culture in Libraries

The technological revolution in information and communication has created new avenues for libraries to deliver library services and information resources to end users. This study elucidates how library and information science professionals (LISP) use information and communication technology (ICT) tools in communicating, storing, and managing library data and convert the information for enhancing the quality of library services and developing a web-based collaborative system culture in libraries. The study provides a practical approach to using Google Drive and has created a web-based collaborative working culture for libraries. Revolutionary technological tools and applications are helping to create/develop easy-to-use platforms that allow professionals and end users to collaborate in both synchronized and non-synchronized modes.
Cosmetic Accounting Practices among Jordanian Firms? The Role of Ownership Concentration and Political Influence.

Cosmetic accounting is a process used by accountants who have a vast knowledge of accounting rules to address the figures reported in the financial reports. This study focuses on the crucial role of the concentration of ownership and the political influence on the quality of earnings among Jordanian industrial firms listed on the ASE during the period 2014-2017. The results of regression indicate that there is a negative impact of both of ownership concentration and political connection on the quality of earnings reported in financial reports. This means that the most significant shareholders use their power, and the political role of board members to manipulate earnings to be consistent with their interests. The study found that other important factors may affect the quality of earnings such as foreign ownership, especially with the migration of some capital to Jordan as a safe environment for investment, particularly under the political and economic tension in neighboring countries.
Tata Kelola Gambaran Perencanaan Media Pembelajaran Berbasis Audio Visual pada Mata Pelajaran Bahasa Indonesia di SMA Negeri 1 Larompong Kabupaten Luwu

The study aimed to determine the picture of audio visual based learning media planning in Indonesian subjects. This type of research is descriptive qualitative to find the nature or experience of a person with a phenomenon that is the governance of audio visual based learning media. Data was collected through: stakeholder involvement through the planning of Larompong 1 High School learning media management. Audio Visual Based learning media governance is obtained through two data sources namely informants and documents. Data collection techniques through interviews, observation, documentation and focus group discussions. The results of the study show: The governance of audio visual based learning media planning begins with the selection of instructional media tailored to the material and learning objectives in the RPP with the principles of using audio-visual media and refers to the Minimum Completeness Criteria. Students who get the KKM value exceeds the KKM value that has been set by the school means that the student has been able to study thoroughly, conversely if students who get the KKM value is smaller and the KKM value that has been set by the school then the student is said to have not finished learning. Students will be given remedial services by subject teachers and for those who have met the KKM, then given enrichment.
FACIAL RECOGNITION, AUTONOMOUS LEARNING, BASED ON IMAGE FRAGMENTATION

This paper uses variations in the image fragmentation approach, considering the number of fragments, number of samples per person, number of hyperplanes and size in the region of interest.Computational vision techniques, in particular gradient histogram (HOG) as feature space descriptor, automatic learning methods, such as vector support machines (SVM) for model construction and a face detection algorithm, are used to replicate these experiments in a real time context.Tests are performed on a population of 40 people, samples taken in uncontrolled situations, in this way some states are discarded, refining the parameters until arriving at a configuration that complies with delivering the best results in this experiment and under these conditions.
Marker Based Optical System for Parametric Rapid Design

The article describes a optical method of measuring macro geometry of body parts for designing wearable devices such as smart watches, sensor supports mounted on arms. Typical precision achieved was 0.1 mm for measuring distances between 2 points marked on a test subject at a distance of 0.5 m. The system utilizes blue light (400 nm) used with photo luminescent materials placed on surface of a object registered by a camera with 600 nm low-pass filter connected to a computer which is running a program for image recognition designed for this task.
Augmented Reality Gaming

This project is completely a Game which will be developed on Augmented Reality technology .The main objective is that to make an efficient Augmented Reality game that is playable on almost every Android devices that is possible.It works by capturing a scene which has more intensity by use of an camera in a device.This project also overcomes the problem of no UI buttons for some AR games which are mostly unofficial.In our project we add UI buttons for the shooting game actions into an AR Concept.It will be developed using UNITY game development engine (Game developing software) with VUFORIA extensions in it with the Vuforia license provided .We use Unity3d and Vuforia to make the players feel as they are surviving in the game.
A Brief Survey on Perils of Data Storage in Cloud

With the dominance of technology, the size of the data is increasing exponentially day by day.Cloud computing serves as an exceptional solution for storage of this rapidly growing data.Cloud computing technology evolves the delivery of computing services such as servers, storage, databases, networks, software, analytics and many more. As the significance of data elevates, a large number of security issues also arises. A lot of questions remain unanswered when we talk about the security of data stored in cloud. This paper presents a brief survey on the issues involved in cloud data storage. We elaborate the already existing ideas, methodologies and experiments recommended by our forerunners and survey the issues that exist in storage of data. We also try to figure out the necessary solutions for these issues concerning other technologies such as block chain that could act as an efficient replacement for cloud.
Deep Learning Model for Motion Video Processing

In the film industry for motion picture processing, it requires different rate (fps) of motion capture.Utilizing single sequence compromises on quality.Different frames are required to be inputted to video editing tools as per motioning requirements.The goal of the paper is to construct a model to utilise the captured frame sequence and generate slow motioning using clustering and Convolutional Neural Networks.
DESIGNING FOR QUANTUM COMPUTING

During the last few years, quantum computing seems to have become a reality.Some few companies have developed quantum computers, and are in use in some large institutions and Universities, while other public organizations have made a similar attempt, but on a smaller scale.Promising to solve otherwise intractable problems for normal supercomputers, companies like Google are already using quantum computers to design solutions, including one allowing the software to distinguish cars from landmarks.However, after numerous and different empirical tests the results are not unanimous, resulting in new attempts to figure out what it is the best way of using this new type of machine that exhibits quantum properties.Developers and scholars argue for the need to redesign quantum computer to achieve full use of this new technology in computers.Proposing a designerly perspective on quantum computing seems a novel and interesting possibility to allow researchers fully taken advantages of this technology.This theoretical paper suggests the use of Design Thinking, and how it is used to solve wicked problems, to re-think how to approach quantum computing.For the design community, understand how to approach, understand and design for quantum computers, may open for a new field of research.