Reviewerly/exHarmony huggingface dataset:
Implementasi E-Learning Sebagai Media Alternatif Pembelajaran Pada AMIK Tunas Bangsa Pematangsiantar

Electronic learning (E-Learning) is a learning method that utilizes the provision of information that can be accessed from anywhere, strong search system capabilities, rich interaction, full support for effective learning and performance based assessments. E-learning has characteristics independent of place and time. Learning methods in AMIK Tunas Pematangsiantar require alternative learning models that do not have characteristics depending on location and time, one of which is to become a learning method that is in accordance with the current pandemic conditions. In addition to the level of proficiency, alternative models are also expected to provide knowledge sharing facilities and knowledge visualization so that knowledge becomes more interesting and easier to understand. This learning information system was built to be run online through the internet using web facilities. The e-learning information system was chosen because it can be used without being time dependent and can be accessed with electronic devices that support the internet, browsers, even though smartphone devices. Today's web is an open source information system that is easy to develop. The E-Learning Information System is implemented using the PHP programming language using the using the MySql database.
초등돌봄교실 문화예술교육 프로그램 개발 방향

Elementary child care classes have been increasing since they were introduced in 2004 due to the increasing social needs for the changing parenting environment and care, and as elementary child care classes increase, the demand for specialized programs including cultural experience, specialty, aptitude, and arts and physical education will also increase.The culture and arts education programs have a similar purpose to the elementary child care class’ group activity program in that it grows creativity and personality through arts, which shows that the culture and arts education program is suitable for the elementary child care classes.Therefore, in order to develop and revitalize the culture and arts education program suitable for the elementary child care classes, we intend to present the development direction so that the culture and arts education program reflecting the characteristics of the elementary child care class can be developed as follows:First, if the child care class is a place to protect children, the child care class’ program should be a time for children to grow their ability to regulate and control themselves. Second, low-grade students should be organized around various cultural experiences through arts, and high-grade students should be organized around contents that can discover and grow their specialty and aptitude. Third, in the annual plan, it is desirable to organize the program with one flow, but to operate each session independently so that achievements are not accomplished over multiple stages. Fourth, it is recommended that the culture and arts education program for elementary child care classes is linked with the elementary child care class’ program and use the teaching materials and teaching tools of the child care classes.This study suggested the development direction of the culture and arts education program for elementary child care classes based on the characteristics and operation of the elementary child care classes. Based on this, it is hoped that programs that children can participate safely and joyfully, programs that can contribute to the fulfillment and internalization of demand for increasing elementary child care class’ program, and various culture and arts education programs suitable for elementary child care classes will be created.
Analyzing Reactions on Political Issues in Social Media Using Hierarchical and K-Means Clustering Methods

Social media usage is undeniably getting larger, Currently, Twitter is one of the most popular social media platforms that enables its user to post their thoughts on anything, commonly in the form of limited word length. The massive number of Twitter users has made Twitter a valuable source of data in analyzing people behavior and tendency in reacting to a certain political issue. Unfortunately, the textual postings are difficult to analyze as the dimension of the data is too high to be clustered. One needs to find the most appropriate method to cluster Twitter posting with an acceptable clustering result. This study presents the clustering of Twitter users based on the most common words used by the users in reacting to a trending political issue. A comparative study between hierarchical clustering and k-means clustering methods are presented and discussed in this study, as well as the word trend or main topic of the issue by histogram and wordcloud.
Efficient and Reliable Secure Cloud Storage Schema of Block chain for Data De-duplication in Cloud

Minimizing Storage space and bandwidth is a challenging task in cloud computing, duplication is the main key term in cloud computing because of large and multiples of digital data stored in single cloud server. Because of rapid usage and expansion of high amount of data, data de-duplication is a challenging task for removing replica related data which has been stored in cloud to reduce storage and space of bandwidth. Secure de-duplication is also a challenging task in cloud storage environment. Convergent encryption based secure de-duplication approach is used traditionally to explore and identify duplicates from multiple users data with de-duplication sharing and uploading data in cloud environment. Because of large volume data, conventional approaches have not meet practical implementation of de-duplication requirements in cloud storage. So we aim that block chain based cloud storage with data de-duplication is the main problem in distributed file storage environment. For predicting dynamic file de-duplication in file sharing of distributed environment, propose a Novel Block chain based Secure De- duplication Authentication scheme (NBSDAS) with high reliability and confidentiality in which the files are distributed to multiple servers and the information of files is recorded on the time-stamped block chain whose central authorities are replaced to automatically decentralize cloud contracts. This proposed approach combined with genetic algorithm to predict and de-duplication with respect to processing dynamic files individually in cloud computing. Security analysis demonstrates that our de-duplication scheme can achieve the proposed security goals while it has limited overhead proved by simulation experiments with comparison to traditional approaches.
Leveraging Machine Translation to Support Distributed Teamwork Between Language-Based Subgroups: The Effects of Automated Keyword Tagging

Modern teamwork often happens between subgroups located in different countries. Members of the same subgroup prefer to communicate in their native language for efficiency, which increases the coordination cost between subgroups. The current study extends previous HCI literature that explores the effects of machine translation (MT) on crosslingual teamwork. We investigated whether automated keyword tagging would assist people's comprehension of imperfect MT outputs and, therefore, enhance the quality of communication between subgroups. We conducted an online experiment where twenty teams performed a collaborative task. Each team consisted of two native English speakers and two native Mandarin speakers. We provided MT support that enabled participants to read all subgroups’ discussions in English before team meetings, but in two forms: with vs. without automated keyword tagging. We found MT with automated keyword tagging affected people's interaction with the translated materials, but it did not enhance translation comprehensibility in the context of teamwork.
‘Sextortion’ scams: Fear, shame used to extort money

Shame and fear can be dangerous weapons when used by scammers to extort money. Most of the time, these threats have no basis in reality.
Generation of all-to-all connections in a two-dimensional qubit array with two-body interactions

All-to-all connections are required in general quantum annealing machines to solve various combinatorial optimization problems. The Lechner, Hauke, and Zoller method, which is used to realize the all-to-all connections, requires many-body interactions in locally connected qubits. Because most of the qubit interactions are two-body interactions, Lechner also proposed the construction of each four-body interaction by six controlled-NOT (CNOT) gates between two qubits. However, it is difficult to construct many CNOT gates. Herein, we show more concrete sequences to produce four-body and three-body interactions based on a two-dimensional solid-state qubit system. We show that the number of operations needed to construct the many-body interactions can be reduced using appropriate pulse sequences. These findings will help reduce quantum computation costs for solving combinatorial problems.
The Commodities News Corpus: A Resource forUnderstanding Commodity News Better.

Commodity News contains a wealth of information such as sum-mary of the recent commodity price movement and notable events that led tothe movement. Through event extraction, useful information extracted fromcommodity news is extremely useful in mining for causal relation betweenevents and commodity price movement, which can be used for commodity priceprediction. To facilitate the future research, we introduce a new dataset withthe following information identified and annotated: (i) entities (both nomi-nal and named), (ii) events (trigger words and argument roles), (iii) eventmetadata: modality, polarity and intensity and (iv) event-event relations.
Investigating Good Teaching and Learning Experiences in the Perspectives of University Students through Social Network Analysis

This study investigated university students’ perspectives on good class and instructional practices through social network analysis. The subjects were 321 students in the third and fourth academic years in a Korean university. The subjects completed four open-ended questions, asking about experience of good class, good instructors’ teaching practice, and their feelings and attitudes when participating in good class. As social network analysis, KrKwic (Korea Key Words in Context) was used to compute word frequencies and analyze semantic network structures and Ucinet Netdraw to assess centrality in the social network, consisting of degree centrality, closeness centrality, and between centrality. The results are as follows. First, students showed 5 keywords to depict what good class is, including ‘understanding’, ‘example’, ‘video’, ‘interest’, and ‘communication’. Second, the characteristics of teaching methods by professors who practice good class indicate ‘assignments’, ‘questions’, ‘understanding’, ‘example’, and ‘feedback’. Third, the top 5 keywords of students’ attitudes as participating in good class are ‘active’, ‘participation’, ‘focus’, ‘listening’, and ‘asking’. Last, keywords depicting desirable class that students most wanted to take next time are ‘assignments’, ‘rewards’, ‘understanding’, ‘difficulty’, and ‘interest’. The findings from this study include the meanings of the semantic network structures of words in the text making up messages. Also this study can provide empirical evidence for educators and educational practitioners in higher education to create effective learning environments.
Analyzing the occurrence of environmental indicator minerals using clustering techniques and mineral networks

&amp;lt;p&amp;gt;Indicator minerals have special physical and chemical properties that can be analyzed to glean information concerning the composition of host rocks and formational (or altering) fluids. Clay, zeolite, and tourmaline mineral groups are all ubiquitous at the Earth&amp;amp;#8217;s surface and shallow crust and distributed through a wide variety of sedimentary, igneous, metamorphic, and hydrothermal systems. Traditional studies of indicator mineral-bearing deposits have provided a wealth of data that could be integral to discovering new insights into the formation and evolution of naturally occurring systems. This study evaluates the relationships that exist between different environmental indicator mineral groups through the implementation of machine learning algorithms and network diagrams. Mineral occurrence data for thousands of localities hosting clay, zeolite, and tourmaline minerals were retrieved from mineral databases. Clustering techniques (e.g., agglomerative hierarchical clustering and density based spatial clustering of applications with noise) combined with network analyses were used to analyze the compiled dataset in an effort to characterize and identify geological processes operating at different localities across the United States. Ultimately, this study evaluates the ability of machine learning algorithms to act as supplementary diagnostic and interpretive tools in geoscientific studies.&amp;lt;/p&amp;gt;
How Powerful Language Could Be in Communication

This study is a qualitative study that explains how strong language could influence someone’s life based on the use of the words in communication. The study used semantics approach in identifying the effective meaning of the words. Language is powerful and a virtue to self-reflection because it is used to communicate in writing, speaking, and even visually. Having language means that we are able to communicate in such a way that others understand us. Language could be in the form of verbal and non-verbal, even sign is also part of it. Language is sound and symbol which is meaningful. It is not only a key component of communication but also a key aspect of identity. Language could shape somebody by means the words we choose to use become a part of who we are. The result of the study shows that the words have the power to raise you, to destroy you, to inspire you, and to anger you. It might take only one word and it has the power to change someone’s life. However, language becomes more powerful when understood by a wider community than just those closest to you. Therefore, understanding the meaning of the language is core to the language users to avoid ineffective communication.
Blockchain-Based Automotive EDI System, The Concept

The rise of the Blockchain Technology is opening new frontiers for existing automotive Electronic Data Interchanges (EDI) data pipeline. It is destined to bring in the enhanced system stability by establishing a seamless (authenticated) relationship between an auto manufacturer, an original equipment manufacturer (OEM), and an auto dealership, and data needs to flow in both upstream and downstream.
Semantic Analysis and Spectrum Modelling Approach for Hand Written English Text Recognition using Neural Network

One of the most common sources of writing media in ancient times was handwritten notes.One of the most natural ways to write characters is through handwriting. A Japanese brush pen is a popular writing instrument that is used in school for practising writing characters.One of the most common degrading factors that influence image visibility and makes them unclear is noise. Pepper salt noise, speckle noise, and holes on billings, for instance, seem to be the most prominent noises found in manuscripts. There are many denoising methods available. We surveyed the literature from both basic and advanced algorithms in this paper.
IMPLEMENTASI METODE VIŠEKRITERIJUMSKO KOMPROMISNO RANGIRANJE UNTUK SELEKSI PENERIMA BEASISWA PENINGKATAN PRESTASI AKADEMIK

The purpose of this research is to make a PPA scholarship selection system in STT-PLN Jakarta. The selection process carried out has weaknesses in selecting more than one criterion which can cause confusion and inconsistent assessments. This study uses VIKOR as a method to determine the rank of scholarship recipients with criteria that have established by the institution: GPA, number of credits taken, extra-curricular achievements, and parent’s income. VIKOR method is Multi-Criteria Decision Making (MCDM) method which can be used to select more than one criterion and focuses on rangking and selecting and determines compromise solutions for a problem with conflicting criteria. Based on the results of calculations using 4 criteria, the VIKOR method has an accuracy rate of 100%. The results showed that VIKOR can help the selection process and determine the appropriate recipients. Also, this method selects and ranks from a set of alternatives and determines compromise solutions.
Guides: Request from Another Library: Policies & FAQs

This guide is provides how-to assistance with interlibrary loan. It will also include WPI's Interlibrary loan policies.
Advancements in Technology and Customer’s Satisfaction with online banking services

Technological advancements refer to computerised financial systems which can be accesses by customers through a number of electronic banking platforms without getting to speak with bank employees. The key and secondary relationships of dimensions (factors) of Technological advancements and Customer Satisfaction is explored in this paper. On the basis of previous studies about the standardized service qualities of automated services and customer satisfaction, a uniform questionnaire was developed by defining and adapting attributes. Data was gathered from a sample of Indian Clients of banks. The collected data was split into two equal-sized sub-samples. An analysis of the Technology based service quality and customer satisfaction dimensions was conducted Using SPSS 21.0 software, exploratory factor analysis (EFA) was performed on half of the collected data. Confirmatory factor analysis (CFA) was performed on the remaining half of the data using AMOS 21.0 software to validate factor structure. The proposed model's unidimensionality, reliability, and validity were empirically checked. AMOS 21.0 was also used to test hypotheses using structural equation modelling to investigate the relationship between Technological advancements and Customer Satisfaction (SEM). This research can aid bank management in determining customers' quality perceptions of Technology based services, allowing banks to develop strategies to improve service quality and customer satisfaction.
The international scientific-practical conference «Science, technology and information in libraries (LIBWAY-2020)»

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Pelatihan Pembuatan Suvenir Aksesori Fashion Khas Kabupaten Malang dengan Teknik Batik Ecoprint Bagi Generasi Muda

Malang Regency is located in East Java. November 28, 760 is celebrated as Malang Regency Anniversary. Malang Regency has a unique culture worldwide, namely Topeng Panji. This mask is an icon of Malang Regency, so you can find many miniatures, t-shirts, and accessories in the form of Panji Mask, but it is rare to find ecoprint batik with the Panji Mask motif. For that reason, the community service provider wants to make ecoprint batik training as a typical souvenir of Malang Regency for the younger generation, namely students at SD Muhammadiyah 8 DAU. The reason for choosing SD is because many materials are found for making batik, namely leaves. Training targets that train creativity, provide skills and provide new insights related to ecoprint batik. The output produced is an ecoprint batik product in the form of a goodie bag. The method used is ecoprint batik training. This activity has 4 steps of preparation, socialization of batik, production process, and evaluation of activities. In preparation, making observations, interviews, signing cooperation, and socializing batik activities. The socialization of batik including the presentation of ecoprint batik material. Ecoprint batik production process. The final step is to evaluate the activity of conducting observations and interviews with batik students. The ecoprint batik making training makes students more creative and has the skills to make batik, especially the batik with the ecoprint mask of the banner as the icon of Malang Regency.
Hierarchical clustering via mutual learning for unsupervised person re-identification.

Person re-identification (re-ID) aims to establish identity correspondence across different cameras. State-of-the-art re-ID approaches are mainly clustering-based Unsupervised Domain Adaptation (UDA) methods, which attempt to transfer the model trained on the source domain to target domain, by alternatively generating pseudo labels by clustering target-domain instances and training the network with generated pseudo labels to perform feature learning. However, these approaches suffer from the problem of inevitable label noise caused by the clustering procedure that dramatically impact the model training and feature learning of the target domain. To address this issue, we propose an unsupervised Hierarchical Clustering via Mutual Learning (HCML) framework, which can jointly optimize the dual training network and the clustering procedure to learn more discriminative features from the target domain. Specifically, the proposed HCML framework can effectively update the hard pseudo labels generated by clustering process and soft pseudo label generated by the training network both in on-line manner. We jointly adopt the repelled loss, triplet loss, soft identity loss and soft triplet loss to optimize the model. The experimental results on Market-to-Duke, Duke-to-Market, Market-to-MSMT and Duke-to-MSMT unsupervised domain adaptation tasks have demonstrated the superiority of our proposed HCML framework compared with other state-of-the-art methods.
Image hiding using upper-lower decomposition technique

Data security is one of the most important sciences nowadays. There is a huge amount of data transferred over the internet each moment and this data should be secured. Steganography is a type of data security technique that is used to hide the secret message into a cover object. Image steganography is the technique that hides an image in another image. This paper proposed a technique that depends on Lower-Upper (LU) decomposition. In the proposed technique LU decomposition is applied for both cover and secret images. The proposed method was tested using different grayscale and color images. The proposed technique achieved high results in terms of Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Normalized Cross-Correlation (NCC). The PSNR for the cover image is ranging from 36 to 44 dB. The similarity between the secret image and the extracted image is 100% and the NCC is 1.
PyMatching: A fast implementation of the minimum-weight perfect matching decoder

This paper introduces PyMatching, a fast open-source Python package for decoding quantum error-correcting codes with the minimum-weight perfect matching (MWPM) algorithm. PyMatching includes the standard MWPM decoder as well as a variant, which we call local matching, that restricts each syndrome defect to be matched to another defect within a local neighbourhood. The decoding performance of local matching is almost identical to that of the standard MWPM decoder in practice, while reducing the computational complexity approximately quadratically. We benchmark the performance of PyMatching, showing that local matching is several orders of magnitude faster than implementations of the full MWPM algorithm using NetworkX or Blossom V for problem sizes typically considered in error correction simulations. PyMatching and its dependencies are open-source, and it can be used to decode any quantum code for which syndrome defects come in pairs using a simple Python interface. PyMatching supports the use of weighted edges, hook errors, boundaries and measurement errors, enabling fast decoding and simulation of fault-tolerant quantum computing.
A new automatic cell smear and laser release system for near-infrared light responsive release of nucleated red blood cells

The predecessor of China Optics was China Optics and Applied Optics Digest, which was founded in 1985. At that time, it was the only retrieval journal in the field of optics in China. At the end of 2008, China Optics and Applied Optics Digest was renamed