Reviewerly/exHarmony huggingface dataset:
Pengaruh Program Literasi Sekolah Terhadap Minat Membaca dan Hasil Belajar IPA Siswa SMP Negeri Kota Tual

Abstract:  This Research Aims to Know the Effect of School Literacy Programs on Students Reading Interest and Learning Outcomes of Senior High School Students in Tual City. The Types of Research Used Are Quantitative Research with Experimental Quasi Design. This Research Data Collection Technique Is Observation, Questionnaire and Documentation. Data Analysis Used in This Research Is Descriptive Analysis and Inferential Analysis. The results showed that there was a significant effect between the influence of school literacy programs on reading interest and had a significant influence of 44.6% on student learning achievement. Keywords: School Literacy Program, Reading Interest, Learning Outcomes.
BioDSL: A Domain-Specific Language for mapping and dissemination of Biodiversity Data in the LOD

Currently, Linked Open Data (LOD) have enabled integrated data sharing across disciplines over the Web. However, for LOD users, in areas such as biodiversity (which massively use the Web to disseminate data), the task of transforming data file contents in CSV (Comma Separated Value) to RDF (Resource Description Framework) is not trivial. We have developed a new approach to map data files in CSV to RDF format based on a domain-specific language (DSL) called BioDSL. Using it, biodiversity data users can write compact programs to map their data to RDF and link them to the LOD. Biodiversity vocabularies and ontologies, such as Darwin Core and OntoBio, can be used with BioDSL to enrich user data. Existing tools are exclusively focused on mapping (CSV to RDF), offering little or no support for linking data to the LOD (interconnecting user entities to LOD entities). They also are more complex to use than BioDSL.
Multiscale Template Matching to Denoise Epigraphical Estampages

Preethi, P. Kasi, Anish Manish Shetty, M. Mamatha, H. R.An epigraph is an engraved inscription from the past. Deciphering, recognizing and understanding the text in such epigraphical documents is mundane work for archaeologists. One of the major tasks in this is preprocessing the document and denoising it into segmentable form in an automated and fast manner. In this paper, we propose a pipelined solution which includes denoising techniques such as nested median filtering followed by a method of multiscale template matching to denoise noisy epigraphical documents. All epigraphs are usually in grayscale and they are converted to binary black and white images using otsu thresholding. Our template matching algorithm has been enhanced to create a mask of all the matched noise. A deep learning technique called Image Inpainting is then used in order to remove the noise and replace it with the respective background. A comparative study is performed with the output of the proposed method with use of novel denoising methods such as Gaussian blur and wiener filters. Human perception can determine that the proposed algorithm provides more satisfactory results. Standard quality measures such as the Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR) are used to show that the integrity of the image with respect to the text remains intact.
The Effect of Work-Learning Interaction on Learning Satisfaction and Learning Transition

최근 인공지능, 사물 인터넷, 빅 데이터 등 첨단정보기술의 발달로 인해 경영환경은 급속도로 변화하고 있으며, 앞으로의 노동시장도 엄청난 변화가 올 것으로 예상된다. 이에 따라 기업은 경쟁 상대 기업보다 더 빨리 변화하고, 학습하고, 행동하는 조직을 구축해야만 지속가능한 시대가 되었 고, 이러한 흐름에 맞춰 우리나라 정부도 평생교육의 일환으로 일-학습병행제를 도입하여 기업체의 체계적 교육훈련을 지원하고 있다. 따라서 본 연구는 일-학습병행제의 성공적인 정착을 위해 일-학습 상호작용의 효과가 학습만족과 학습전이에 미치는 영향을 검증 하였다. 연구결과, 일-학습 상호작용은 학습만족과 학습전이에 긍정적인 영향을 미치는 것으로 나타났다. 또한 학습만족은 학습전이에 긍정적인 영향을 미치는 것으로 나타났다. 그리고 성취 욕구는 학습-일 상호 작용과 학습만족 간의 관계에서 조절적 영향을 미치는 것으로 나타났다. 본 연구를 통하여 일-학습병 행제의 중요성을 인식하고, 일-학습병행제의 활성화를 위한 전략적인 방향성을 제시하였다는 점을본 연구의 의의라 할 수 있다.Recently, due to the development of advanced information technologies such as artificial intelligence, Internet of things and big data, the business environment is changing rapidly, and the future labor market is expected to change enormously. As a result, global companies have become more sustainable by establishing organizations that change, learn, and act faster than their competitors, and it becomes a sustainable age. Therefore, this study confirmed and verified the effects of work-learning interactions on learning satisfaction and learning transition, for the successful settlement of work-learning parallelism. The results of this study are as follows: have a positive effect on learning satisfaction and prior learning. Also, learning satisfaction has a positive effect on learning prior to learning. And the achievement desire have a moderating effect on the relationship between learning-work interaction and learning satisfaction. The significance of the work-learning parallelism system is recognized through this study, and the strategic direction for the activation of the work-learning parallelism system.
Testing a quantum annealer as a quantum thermal sampler

Motivated by two recent experiments in which thermal properties of complex many-body systems were successfully reproduced on a commercially available quantum annealer, we examine the extent to which quantum annealing hardware can reliably sample from the thermal state associated with a target quantum Hamiltonian. We address this question by studying the thermal properties of the canonical one-dimensional transverse-field Ising model on a D-Wave 2000Q quantum annealing processor. We find that the quantum processor fails to produce the correct expectation values predicted by Quantum Monte Carlo. Comparing to master equation simulations, we find that this discrepancy is best explained by how the measurements at finite transverse fields are enacted on the device. Specifically, measurements at finite transverse field require the system to be quenched from the target Hamiltonian to a Hamiltonian with negligible transverse field, and this quench is too slow. We elaborate on how the limitations imposed by such hardware make it an unlikely candidate for studying the thermal properties of generic quantum many-body systems.
Lists, Mappings, and Objects

So far, we have been using simple types to implement our scenarios. In this chapter, we will be looking into the structural and behavioral types that are available in Ballerina. These types will help us in modeling and solving complex problems more efficiently.
Assessment Design with Automated Scoring in Mind

Work on automated scoring of open-ended responses began with essay scoring and has now advanced to scoring other types of performance assessment like activity in games and simulations. What should be the considerations in assessment design when using complex scoring mechanisms? How much does automated scoring drive other components of design? In this chapter, we provide a brief introduction to principled assessment design generally and present a writing example and a game-based assessment example that are used to illustrate principles throughout the chapter. These examples present challenges around the granularity of student models, designing tasks the produce good evidence, designing for reusability, balancing human and machine scoring in evidence identification, and designing for automated feedback. In the main portion of the chapter, we lay out five principles of assessment design to address these challenges.
LibGuides: How to Request Materials Through Interlibrary Loan: Book Delivery: Statewide Campuses & Online Students

This guide will walk you through how to request materials, free to you, through Interlibrary Loan!
Pengembangan Multimedia Interaktif Materi Sistem Peredaran Darah pada Siswa SMP KELAS VIII

Abstract:   Interactive multimedia is a combination if various media (file format) in the form of text, image, graphics, sound, animation, video, etc. that are integrated and packaged into digital files, can be used and controlled by the user so that the message of learning material optimally accepted by students. Research development aims to determine: 1) the validity, 2) the practivality, and 3) the effectiveness of interactive multimedia on the material circulatory system in humans. This research used 4D model, namely: 1) Establish and define the terms of learning, 2) Prepare prototype learning devices, 3) Produce revised learning devices based on input from experts, 4) use of devices that have been developed on a wider scale. The results of the study show: 1) interactive multimedia circulatory system material in humans developed by this researcher declared valid by the validator. 2) Based on the teacher’s response and the response of students, the interactive multimedia circulatory system material in humans developed by this researcher was declared practical Achievement of student learning outcomes after the application of interactive multimedia to circulatory system material in humans developed by this researcher is stated to have met the effectiveness criteria. Keywords: Interactive multimedia, human circulatory system
Cyber Crimes : A Challenge To E-Commerce

This is an age of Information Technology. It encourages every dimension of human’s life. Electronic commerce consists of the purchasing and disposing of products or services over electronic systems of the computer networks. This paper attempts to focus on the meaning and the growth of E-commerce in India and to study the affect of cyber-crimes on E-commerce. This paper focuses on not only on the understanding of the cyber crimes but also explains the impacts over the different levels of the society while dealing with e-commerce. In India prospect of e-commerce is very bright as business on e-commerce in increasing trend but pace of cyber crimes is also faster. This is a hindrance in growth of e-commerce. Always beware and vigilant approach will help to the community to secure all the online information and e-commerce business which are not safe due to such cyber crimes. The ways to overcome these crimes can be done by enforcing Cyber Laws effectively i.e. education and policy making.
LibGuides: Selective Depository Resources: Home

This guide provides access to information for selective depositories in the Federal Depository Library Program located in Utah and Nevada. USU Libraries serves as the Regional Depository for these libraries.
DEVELOPING ENGLISH MATERIALS BASED ON CHARACTER BUILDING FOR MANAGEMENT CLASS IN STIE CENDEKIA

Nowadays character building is a national movement in Indonesia. The educators are asked to integrate it in the learning process, but unfortunately, there are still many lectures that still have difficul in integrating character building in classroom. In English class character building can be integrated through inserting culture in the material, therefore the students are not only learning about the material but they also learn about the value of the culture. The purpose of this research is to develop English material for management class based on character building. Research and Development (R&amp;D) by Borg and Gall (1983) was applied. The subjects of the research were the English lecture of management class and the students of the fourth semester. The result of the research showed that the instructional materials developed is appropriate to the students’ needs and curriculum.
Online course: IFRS 16 Leases

Get an understanding of the key requirements of the new leases standard IFRS 16 and the issues associated with implementing it.
Supervised Learning for Aggression Identification and Author Profiling over Twitter Dataset

This chapter briefly discusses two essential aspects of the author, namely, the author's aggression and the author's profile. The identification of aggression is classified into three classes, overt, covert and non-aggressive. On the other hand, profiling identifies two properties, age and gender. The chapter also explains various machine learning concepts incorporated into deep neural networks. It also provides insight into the previous work done on author aggression and profile identification. For the purposes of this experiment and in-depth analysis, Twitter and Facebook datasets are used. All of the proposed architectures perform on average better than state-of-art models. For English Twitter, the aggression model achieves 60.09% accuracy and the profiling model can achieve 68.02% accuracy.
Image Classification with Fisher Feature Analysis

Currently, CNN-based scene classification algorithms have become mainstream. By using the features of convolutional neural networks, we propose an image classification method with Fisher feature analysis. Rich high-dimensional image descriptors can be learned through convolutional neural networks, and it is inefficient to calculate the similarity of these high feature descriptors. In order to reduce the time of feature matching and improve the accuracy of similarity descriptor matching, the algorithm adds a hidden layer between the fully-connected layer and the output layer which fine-tuning network to learn the features of low images. For solve the similarity of image feature descriptors, we use Fisher discriminant to classify images which enhance the independence between sample features. Experiments based on the Scene-15 and cifar-10 datasets show that the proposed method improves the efficiency of network feature matching and classification accuracy.
Compact Surjective Encoding Autoencoder for Unsupervised Novelty Detection.

In unsupervised novelty detection, a model is trained solely on the in-class data, and infer to single out out-class data. Autoencoder (AE) variants aim to compactly model the in-class data to reconstruct it exclusively, differentiating it from out-class by the reconstruction error. However, imposing compactness improperly may damage in-class reconstruction and, therefore, detection performance. To solve this, we propose Compact Surjective Encoding AE (CSE-AE). In this model, the encoding of any input is constrained into a compact manifold by exploiting the deep neural net's ignorance of the unknown. Concurrently, the in-class data is surjectively encoded to the compact manifold via AE. The mechanism is realized by both GAN and its ensembled discriminative layers, and results to reconstruct the in-class exclusively. In inference, the reconstruction error of a query is measured using high-level semantics captured by the discriminator. Extensive experiments on image data show that the proposed model gives state-of-the-art performance.
Distributed Ledger Technology in the Banking Sector: A Method for the Evaluation of Use Cases

Distributed ledger technology (DLT) is seen as an opportunity for the banking sector with high potential to achieve complexity reduction, cost savings, and further benefits in diverse processes. These high expectations and a limited technology know-how lead to bank internal challenges during the selection of suitable use cases for DLT. We apply Design Science Research (DSR) to address this challenge by developing a method for evaluating the business needs and the feasibility of deploying DLT in a certain use case in the banking sector. Devised using the letter of credit (LC) process as reference, our results suggest that various requirements and beside bank internal also external parties should be included in the evaluation. This implicates, that a more detailed study is needed on including external stakeholders in use case evaluation. Our method can be customized and applied as a structured evaluation approach in the banking sector.
Comparison of Hedging Devices in Published Research Articles by Indonesian and English Native Writers: A Corpus Based Study

Abstract : This study aims to compare how Indonesian and English Native writers use hedges in their published research articles. The source of data was 40 research articles published in English written by Indonesian and English Native writers. The study investigated three sections of each research article (Introduction, Discussion, and Conclusion) where hedging devices are usually used. To get the hedge frequencies, the data were analysed using concordance program called AntFileConverter (1.2.1) and AntConc (3.5.0). The types of hedges were categorized based on hedges taxonomy adapted from Selager-Meyer. The result of the study provides the implication that Indonesian scholars need a special instruction especially which focus on hedges proposition. Key Words : hedges, research articles, corpus based study Abstrak : Penelitian ini bertujuan untuk mengetahui bagaimana penulis Indonesia dan penutur asli bahasa Inggris menggunakan hedges pada artikel penelitian terpublikasi. Sumber data diambil dari 40 artikel berbahasa Inggris yang ditulis oleh penulis Indonesia dan penutur asli bahasa Inggris. Penelitian terfokus pada tiga bagian utama dari artikel penelitian (Pendahuluan, Diskusi, dan Kesimpulan) dimana hedges sering digunakan. Untuk menghitung frekuensi hedges , data dianalisis menggunakan program kecocokan, yaitu AntFileConverter (1.2.1) and AntConc (3.5.0). Tipe hedges dikategorikan menurut taksonomi yang diadaptasi dari Selager-Meyer. Hasil penelitian memberikan implikasi bahwa para praktisi pendidikan Indonesia memerlukan intervensi pedagogis yang dirancang khusus untuk membekali mereka dengan pengetahuan tentang hedges. Kata kunci : lindung nilai, artikel penelitian, studi berbasis corpus
Improving 3D Measurement Accuracy in Epipolar Directions via Trinocular Spherical Stereo

Spherical cameras are suitable for all-round 3D measurement due to their wide field of view. When performing 3D measurement using binocular spherical stereo, the areas in the epipolar directions cannot be reconstructed accurately due to the low measurement confidence in the epipolar direction. By adding one more spherical camera, perpendicular to the epipolar direction, to the binocular spherical stereo to form a trinocular spherical stereo, all-round 3D measurement can be achieved. In this paper, we propose a method to improve the 3D measurement accuracy by minimizing the overall reprojection error. Effectiveness of the proposed method is verified through experiments.
INVESTIGATING THE FACTORS INFLUENCING STUDENTS' WILLINGNESS TO COMMUNICATE IN ENGLISH

This paper aims to investigate the factors that affect the students’ willingness to communicate in English in the classroom. This study employs a qualitative method, particularly the case study with the use of observation, questionnaire, and interview to collect the data. It can be concluded that there are mainly five factors that influence students’ willingness to communicate namely teachers, topic discussions, classroom environment, peers, and types of activities.
Classification of Clothing Using Convolutional Neural Network

This paper presents classification of an image as shirt, T-shirt or trouser for a specific objective by training a convolutional neural network (CNN). The classifier implemented is a significant component of the assistive instrument developed to help people with dementia become more independent with dressing. The work presented in this paper brings out tuning the hyperparameters of the CNN used in the system. A dataset was prepared for the three classes of clothing by capturing the images, pre-processing and labelling the images. Data augmentation was performed on a subset of the original dataset to reduce the overfitting problem. A standard architecture was chosen with convolution, max-pooling and dropout filters which help in dimension reduction, thus enabling faster training of the model. Upon evaluation of the model on the testing dataset, an accuracy of 93.31% was achieved. In order to describe the performance of the classification model, a confusion matrix was plotted.
The Effects of Blended Learning on University Students’ TOEIC Achievement

The purpose of this study is to find out the effects of blended learning method for the class for TOEIC test. For this study, 50% of general lectures were conducted, and 50% of the lessons using blended learning method were provided to 117 university students. Their progress were tested twice, and the students
The Research on the Theme and Development Trend of Mobile Learning in China in the Past Ten Years

Mobile learning has become a normal learning mode. It not only seeks innovation in terms of learning time and learning space but also has in-depth research in technical support, learning design, learning model and teaching practice. This paper has used UCINET, SPSS and Citespace to analyze the mobile learning literatures of recent ten years and analysed research topics and development trends of mobile learning using time-space analysis of literatures、 social network analysis、 analysis of highly cited documents and multidimensional scaling.
Computing thermodynamic observables on noisy quantum computers with chemical accuracy

Thermodynamic properties of molecules are vital to chemistry, astronomy, biology, and other fields. Where thermodynamic observables cannot be measured, computational methods are required to fill in the blanks. This typically requires several steps: (i) calculation of the Born-Oppenheimer potential energy surface (BOPES); (ii) determination of intramolecular vibrational modes; and (iii) calculation of the partition function and thermodynamic observables. Typically, the first step is the computational bottleneck since it requires solving the Schrodinger equation, a task that quantum computers have the potential to accelerate beyond what is possible using classical computers. Quantum computers have been constructed that manipulate entanglement and superposition of qubits and thus operate on quantum states. In conjunction with hybrid quantum-classical algorithms, these machines can approximate solutions to the Schrodinger equation. So far, noisy quantum computers have been used to compute the BOPES of small molecular systems (step i, above). However, these calculations are often too noisy for the determination vibrational modes (step ii) using traditional methods. Here, we report a method to compute thermodynamic observables using electronic energy calculations executed on a superconducting-qubit quantum computer. We calculate the BOPES of hydrogen using the variational quantum eigensolver algorithm, which is passed to a classical computer to compute the parameters for the Morse potential, which mitigates the noise and provides vibrational energy levels. Next, the partition functions of hydrogen, deuterium, and hydrogen deuteride, are calculated, from which we obtain thermodynamic observables. Compared to experimental data, we have achieved chemical accuracy for internal energy, entropy and heat capacity for these molecules and for their isotopic exchange reaction.
UEWDM NAVIGATIONAL DESIGN: A CASE STUDY OF APU WEB ATTENDANCE

The process of designing web application has become a challenge for many individuals, specifically web developers due to interaction processes involvement in the design process. The designs should incorporate conceptual aspect, interaction processes, navigation structures and abstract presentation design. Unfortunately, many practitioners believe that most of the web applications have been developed in an ad hoc manner and less focus on the interaction processes. As a solution, UEWDM has been proposed in order to deal with the issues mentioned above. Thus, in this paper, APU web attendance is presented as a case study of UEWDM in order to verify that the proposed design model is applicable to any web application design with interaction processes. Researchs contribution relies on the expressive web design model of navigational design, which utilizes UML stereotypes for the interaction processes modeling. In other words, UEWDM could act as a guideline and assist web designers in designing web applications that consist of interaction processes.