Reviewerly/exHarmony huggingface dataset:
Design and Implementation of Command-and-Control Voice User Interface for Server Management Systems

Voice interface technology is a technology that enables dialogue between machines and humans by using ‘words’, one of the most natural means of communication for humans. One of the advantages of using the voice interface when entering commands is that it can be used in parallel with the keyboard interface. Therefore, usability can be improved by supporting a voice user interface in softwares running on computer servers or PCs. In this study, a command-and-control interface was designed and implemented for a multi-server management system that manages multiple servers. The command input mode used voice and keyboard, and the information output mode used the screen and beep interface. The voice recognizing software can be run in a web browser and uses the open source Annyang library. The results of this study are expected to be utilized in the design of voice user interfaces for application software, facility management software, and IoT device monitoring systems for professional users.
An Empirical Study of R Applications for Data Analysis in Marine Geology

The study focuses on the application of R programming language towards marine geological research with a case study of Mariana Trench. Due to its logical and straightforward syntax, multi-functional standard libraries, R is especially attractive to the geologists for the scientific computing. Using R libraries, the unevenness of various factors affecting Mariana Trench geomorphic structure has been studied. These include sediment thickness, slope steepness, angle aspect, depth at the basement and magmatism of the nearby areas. Methods includes using following R libraries: {ggplot2} for regression analysis, Kernel density curves, compositional charts; {ggalt} for Dumbbell charts for data comparison by tectonic plates, ranking dot plots for correlation analysis; {vcd} for mosaic plots, silhouette plots for compositional similarities among the bathymetric profiles, association plots; {car} for ANOVA. Bathymetric GIS data processing was done in QGIS and LaTeX. The innovativeness of the work consists in the multi-disciplinary approach combining GIS analysis and statistical methods of R which contributes towards studies of ocean trenches, aimed at geospatial analysis of big data.
INCREASING STUDENTS’ VOCABULARY OF VII GRADE AT SMP N 3 TOLITOLI THROUGH WORD SEARCH PUZZLE

The objective of the research is to prove whether word search puzzle can be applied to increase students’ vocabulary.. This pre-experimental study uses 33 students as a sample. They are grade VIIf of SMP N 3 Tolitoli. The procedure of this research consists of pretest, treatment, and posttest. The result of the analysis shows that word search puzzle contribute greatly to the students’ vocabulary.. It can be seen by the difference of the mean score between pre-test and post-test. The mean score of pre-test was 76.09 while in the post-test improved up to 84.61. The data of this research are analyzed by using SPSS Program version 16.0. Then the data of both tests are analyzed by using T-test, and the result shows that the T-test value 11.818 is high than T-table value 2.037. It can be inferred that word search puzzle was very effective to increase students’ vocabulary.  Keywords:  Increasing, vocabulary, word search puzzle
The Enlightenment of Discourse Analysis on College English Reading Teaching

Language form teaching is the main teaching method for many teachers to carry out English classes. Although it can enable students to complete the mastery of knowledge to a certain extent, this teaching method that ignores the cultivation of their reading ability and language application ability is not only for students. The enthusiasm of learning is a kind of inhibition, and it will also affect its learning effect to a great extent. Therefore, when the English reading class is carried out, the introduction of discourse analysis teaching methods will help students learn knowledge while training their learning ability and reading ability, hoping to promote the comprehensive development of students and ensure the smooth teaching in the classroom carry out.
Semantic similarity measurement: an intrinsic information content model

Ontology dependent Semantic Similarity (SS) measurement has emerged as a new research paradigm in finding the semantic strength between any two entities. In this regard, as observed, the information theoretic intrinsic approach yields better accuracy in correlation with human cognition. The precision of such a technique highly depends on how accurately we calculate Information Content (IC) of concepts and its compatibility with a SS model. In this work, we develop an intrinsic IC model to facilitate better SS measurement. The proposed model has been evaluated using three vocabularies, namely SNOMED CT, MeSH and WordNet against a set of benchmark data sets. We compare the results with the state-of-the-art IC models. The results show that the proposed intrinsic IC model yields a high correlation with human assessment. The article also evaluates the compatibility of the proposed IC model and the other existing IC models in combination with a set of state-of-the-art SS models.
Students’ attitudes on electronic English learning

Along with the development of technology in various aspects of life, it makes technology have a big impact and influence in today's life. In educational sector, one of the roles of technology in learning activities is to support the learning activities become easier to accomplished and interesting. One of the developments of technology in education sector is E-Learning. E-Learning may be an option to be used on class as a learning tool. Especially, on English subject when some students may find it difficult then E-Learning could be their alternative to learn English the significance of this study for find out the students’ perspective regarding E-Learning in English subject. The data will be conducted by distribute questionnaire to students. The objectives of this study are to find out attitudes from students toward E-Learning. The study conducted in Bunga Bangsa Islamic Junior High School involving 56 students. Questionnaire was used as an instrument to collect the data which score analyzed based on the mean score. The result showed students have positive attitudes toward E-Learning. In terms of students’ attitudes, it is found that students have positive attitudes toward E-Learning since they found E-Learning is appropriate to use, effective, and excellent technique to help them learning English.
Propagation of Well-Log Data Imputation Uncertainties Towards the Interpolated 3D-Petrophysical Map Using Epistemic Kernels and Kriging

Summary In this work, we present a method for propagating the uncertainties related to a well-log data imputation procedure towards the interpolated 3D-Petrophysical map using epistemic kernels and kriging. We introduce the concept of epistemic kernels which bring a convenient way of incorporating the uncertainty related to the lack of knowledge about the true (observed) value of a variable into the covariance and variogram matrices. An advantage of doing that is that we don’t modify the kriging equations to incorporate such uncertainties, all is done by the kernel. We conduct an experimental study to support our claims using well-log data from the New Zealand repository. We showed that those epistemic kernels when used in Ordinary kriging, avoid optimistic estimates of the variances of the predicted 3D-Petrophysical map when a well-data source contains imputed values.
Perancangan Layout Katalog Cetak Photobox.Id Sebagai Media Promosi

The design of this work aims to provide information about the services offered by Photobox.id and make it a media campaign. The formulation of ideas for creating this work is that creators are encouraged to design layouts for the Photobox.id catalog. The media used in catalog layout design is print media that is interesting to read using design techniques so that readers can enjoy and give a comfortable impression when reading the catalog. The method of making this work is done by studying literature through books, internet and field studies, namely observation, interviews with owners and clients from Photobox.id. The work created by the creator will be in the form of a printed catalog book, where there are illustrations or photos that represent every content that exists and give an impression, neat, clean, simple and modern. The conclusion of this work is that catalog layout design plays an important role as a medium for promotion and corporate identity. Illustrations or photos that can be very supportive elements in designing catalog layouts, where each element can represent existing content.
Bayesian Nonparametric Clustering as a Community Detection Problem

It is well known that a wide class of bayesian nonparametric priors lead to the representation of the distribution of the observable variables as a mixture density with an infinite number of components, and that such a representation induces a clustering structure in the observations. However, cluster identification is not straightforward a posteriori and some post-processing is usually required. In order to circumvent label switching, pairwise posterior similarity has been introduced, and it has been used in order to either apply classical clustering algorithms or estimate the underlying partition by minimising a suitable loss function. This paper proposes to map observations on a weighted undirected graph, where each node represents a sample item and edge weights are given by the posterior pairwise similarities. It will be shown how, after building a particular random walk on such a graph, it is possible to apply a community detection algorithm, known as map equation method, by optimising the description length of the partition. A relevant feature of this method is that it allows for both the quantification of the posterior uncertainty of the classification and the selection of variables to be used for classification purposes.
Sixth Sense on Personal Assistance

This paper mainly focuses on dealing with the problems faced by the deaf and the dumb community in India in using the future technologies mainly personal assistance tools, may it be Alexa home or Amazon echo. We propose to make use of the standard Indian sign language as well as the sign language dictionary to create a manual entries of sign languages to a user interface which makes use of these sign language dictionary to convert the signs shown by a speech or noise impaired person by taking inputs from digital cameras or the laptop cameras in order to convert them into speech and made useful to the personal assistance tools that just takes audio voice as inputs. It is built by using machine learning tools which includes a TensorFlow library package. The whole project is user made to be user friendly to the community that will make use of it the most as well as easily understandable by the personal assistance tools in use worldwide. The project promises to ease the work of a speech disabled individual may it be through easy conversion of sign languages for a video call which helps the receiver get written transcripts of the signs displayed by the individual on the other end. However the main purpose of the project is with the purpose of helping such individuals make use of personal assistance tools which poses as an essential tool in the future to come.
Identifying Similar Users Based on Their Check-in Data: A Graph Embedding Approach

In recent years, the amount of user check-in data has significantly increased on social network platforms. Such data is an ideal source for characterizing user behaviors and identifying similar users, contributing to many research areas (e.g. user-based collaborative filtering). However, existing trajectory-based user similarity analysis approaches do not distinguish the effects of geographical factors at a fine-grained level, and thus are not able to unleash the full power of semantic information that is hidden in the trajectory. In this paper, we have proposed an effective graph embedding approach to identify similar users based on their check-in data. Specifically, we firstly identify meaningful concepts of user check-in data, based on which we design two metagraphs for representing features of similar user behaviors. Then we characterize each user with a sequence of nodes that are derived through a metagraph-guided random walk strategy. Such sequences are embedded to generate meaningful user vectors for measuring user similarity and eventually identifying similar users. We have evaluated our proposal on three public datasets, the results of which show that our approach is 4% higher than the best existing approach in terms of F1-measure.
MENGENALKAN PEMIKIRAN PIERRE BOURDIEU UNTUK SASTRA ELLY PRIHASTI WURIYANI

Abstract  Pierre Bourdieu's thought has become an alternative to analyzing the battles waged by the author in the process of ideas, writing, to publication. This reason becomes the basis and consideration that literary studies can enter many domains, not only in literary works but also in authors, society and publishing. Pierre Bourdieu offers the concepts of habitus, capital, realm, and practice. The description method and application method are used to understand Pierre Bourdieu's concept of thought and application to continue the literary work. The result was that Lena Simanjuntak fought in her OBPdPD so she could do shows from 2013 to 2017. Keywords: battle, Perre Bourdiau, Literature, Writer
Towards Scalable Retrieval of Human Motion Episodes

With the increasing availability of human motion data captured in the form of 2D/3D skeleton sequences, more complex motion recordings need to be processed. In this paper, we focus on the similarity-based retrieval of motion episodes - medium-sized skeleton sequences that consist of multiple semantic actions and correspond to some logical motion unit (e.g., a figure skating performance). We examine two orthogonal approaches to the episode-matching task: (1) the deep learning approach that is traditionally used for processing short motion actions, and (2) the motion-word technique that transforms skeleton sequences into a text-like representation. Since the second approach is more promising, we propose a two-phase retrieval scheme that combines mature text-processing techniques with application-specific refinement methods. We demonstrate that this solution achieves promising results in both effectiveness and efficiency, and can be further indexed to implement scalable episode retrieval.
Ensemble of Multiple Kernel SVM Classifiers for Detection of Online Spam Reviews

The Social web contains enormous content, in which higher range of online users believe the Online Reviews for their decision making before any online purchase or using services. The online reviews written are all not true. Some of the Reviews are Spam for many reasons. Data Mining Classification provides good solution to find the Review as Spam or Ham. SVM(Support Vector Machines) classifier is the most frequently used classifier. There are proven record of achieving high performance through SVM Classifier during classification of all kinds of data especially text data for binary classification. Ensemble of Multiple Kernels such as SVM-Polynomial, SVM-Linear, SVM-Sigmoid, SVM-RBF(Radial Basis Function) of SVM improves the classifiers performance in a significant way.
Ranked dropout for handwritten digit recognition

Overfitting is a common problem in training of neural network with small training sets, which leads to worse performance on the new samples. Dropout has been proved to be an effective method to avoid overfitting, which prevents co-adaptation of features detectors by randomly discarding nodes from hidden layers of network. Inspired by dropout, we proposed a ranked dropout method to remove randomness of standard dropout mask, which discards a part of active nodes and forces the inactive nodes to learn more features to improve generalization ability. We apply the proposed ranked dropout to a stacked autoencoder network and compare it with standard dropout, gaussian dropout, uniform dropout and DropConnect on MNIST dataset. Experimental results of handwritten digit recognition demonstrate that the ranked strategy leads to better classification performance and the proposed ranked dropout can effectively reduce interference of overfitting and improve model‟s generalization ability.
Multi-criteria Group Decision-Making Method Based on D Numbers

Investment decision is an important aspect of multi-criterion group decision-making (MCGDM). Investment decision-making is a complicated problem because it is decided by many factors together, and there are many kinds of uncertainties in each factor. Many theories has been put forward which express and process uncertain information. And yet, these theoretical methods have some disadvantages and deficiencies. Recently, a new theoretical method, which represent and process uncertain and incomplete information, is proposed, it is called  number, and it has been tried in many fields. In this paper, we propose to transform intuitionistic interval number into  number on the basis of  number theory and intuitionistic interval number theory, and use  number to express and process uncertain information. After that, through a concrete example of investment decision, the feasibility of the new method is further verified the principle of the proposed method is easy to understand, the calculation is simple and easy to operate, more importantly, the ranking decision can be made easily.  In addition, there's a lot of evidence to suggest that the proposed method can be applied to other fields.
The Lawyer's Cryptionary: A Resource for Talking to Clients About Crypto-Transactions

This paper contains a number of terms important for understanding the developments that are taking place in the crypto community. Because change is happening so rapidly, it is extremely difficult to stay current on the terms, concepts and issues relevant to blockchain, cryptoassets, and the regulation of ICOs and other cryptotransactions. This paper creates a “cryptionary” of alphabetized terms that should make much of what is being written in the space more understandable. The paper also makes note of terms as to which there is considerable ambiguity over meaning, and includes an assessment of the most common or more useful definitions where appropriate. To the extent possible, explanations assume that the reader does not have a technical background and is not already familiar with the topics discussed.
(Un)Corporate Crypto-Governance

Public blockchain protocols face a serious governance crisis. Thus far, blockchain protocols have followed the path of early Internet governance. If the architects of blockchain protocols are not careful, they may suffer a similar fate — increasing governmental control, greater centralization, and decreasing privacy. As blockchain architects begin to consider better governance structures, there is a legal movement underway to impose a fiduciary framework upon open source software developers. If the movement succeeds, the consequences for open source software development could be dire. If arbitrarily imposed upon blockchain communities without consideration of variances among communities or the reality of how such communities operate, the movement may quash the technology before it ever matures. Further, in its present iteration, the argument for imposing fiduciary duties is not limited to the blockchain context and could easily be extended to other open source projects. Such open source projects have not been subject to this fiduciary responsibility scheme and yet have been an important force in industry and society for decades. Instead, this Article argues that blockchain architects should consider adopting contracts that rely upon corporate governance models for inspiration. Such a model would not obliterate the notion of fiduciary responsibilities in blockchain governance, but rather, allocate such responsibility in light of the actual mechanics of the technology. The model also enables a scheme of heightened responsibility for a greater number of actors in the ecosystem under certain circumstances. Furthermore, a contractually based governance system mirroring corporate governance paradigms would offer blockchain protocols an opportunity to adopt governance rules that reflect the unique goals and culture of the protocol and its community while appeasing the regulator’s need for a legally recognizable and responsible hierarchy. Although there will be cultural challenges to governing blockchain protocols through a corporate law model, the Article concludes that navigating such challenges is not only possible, but offers and opportunity to encourage new corporate governance structures in more traditional enterprises.
영어의 읽기와 쓰기 관계 연구: 영어 문법 및 어휘 능력과 전공 계열이 미치는 조절 효과를 중심으로

The present study reported on the directionality of the relationships between reading and writing in English and the effects of background knowledge(i.e., English vs. non-English major group) and English proficiency in moderating these relationships. Results of the present study show that a bi-directional and interactive model of reading-writing relationship fit better the English major group, while a reading-to-writing model was better supported by the data for the non-English major group. With regards to the moderating effects of English proficiency, it was found that the strength of the relationships between reading and writing did not significantly differ according to the level of English proficiency in the English major group. However, in the non-English major group, English proficiency significantly moderated the effects of reading on writing, but it did not significantly moderate the effects of writing on reading. Pedagogical implications are also provided.
Evaluating immersive and non-immersive VR for spatial understanding in undergraduate construction education

In this paper we explore a pedagogical value of using immersive vir-tual reality to teach construction students how to identify and evaluate the spa-tial characteristics of their design in terms of sizes, layout or structural issues. This study builds on the premise that virtual reality, though generally valuable for design understanding, cannot be treated as a monolithic system when it comes to evaluating its effectiveness for tasks that differ in their objectives. The study extends the work of similar studies that have looked into the claimed ben-efits of immersion, stereoscopy or interactivity on visual perception and spatial cognition. We compared a desktop-based environment with a fully immersive virtual reality in the form of a wearable VR headset to see if there are any no-ticeable differences in how students review and evaluate spaces. Thirty-two par-ticipants from the first year undergraduate construction program were tasked to walk through a small residential house that incorporated up to 12 intentional de-sign mistakes in terms of the size, layout, position or structural oversight. Initial results suggest that the students using the HMD-type of VR slightly better per-form compared to those using the monitor. However, observations of students’ interactions with the model while completing the tasks suggest a greater com-plexity in how the navigation patterns, domain knowledge and technology expe-rience may be affecting the way they perceive the design.