Reviewerly/exHarmony huggingface dataset:
SPEECH ACTS ANALYSIS IN COLLEGE DISCOURSE AT THE ENGLISH DEPARTMENT OF MUHAMMADIYAH UNIVERSITY OF MATARAM IN ACADEMIC YEAR 2016/2017

In expressing something, speakers showed an action. This action could make the listeners easier to know what the speakers intended to. This is called speech act. The purpose of this research was to analyze the types of speech act used in college discourse at the English departement of Muhammadiyah University of Mataram. The researcher used those speeches as the data. The researcher took 14 students of English departement at Muhammadiyah University of Mataram as the participants. Observation was used as the data collection procedure. The result of research revealed that the aspects of speech act used at the college discourse analyzed by the researcher were: locutionary act, illocutionary act, and perlocutionary act. From those three aspects analyzed by the researcher, illocutionary act was the most often used in college discourse at the English departement of Muhammadiyah University of Mataram.
OCR to read embossed text from Credit/Debit card

This paper is based on a real application in which the task was to recognize the digits and characters embossed on the credit/debit card i.e the card number and the expiry date. The problem was that the digit embossed are uneven. Using tesseract for OCR was not enough to recognize the digits accurately. The first problem was that to separate the digits and the second fact was that the separated characters or digits were distorted heavily. Challenge is to recognize the digits correctly. In this paper, we present an algorithm for credit/debit card number identification based on Optical Character Recognition using KNN. The algorithm is tested on five hundred credit and debit card images of different illumination of lights. When the images have captured the angle of view and distance were taken into consideration. The images were then preprocessed using an image processing algorithm. The resultant images were then fed to the OCR system. The achievement of this work was the correct identification of digits with 90% and zero false identification.
Rancang Bangun Aplikasi Pengolahan Data Bank Sampah Berbasis Web (Studi kasus Pada Rungkut Lor GG.III RT.03 RW.06)

Garbage Bank in Rungkut Lor Gg. III RT. 03 RW.06 Surabaya is an environmental group engaged in environmental health, this activity is carried out by community representatives, and its customers are also local RT community. The garbage bank Rungkut lor Gg. III RT. 03 RW. 06 is carried out once a month in the RW hall to weigh the garbage. The people resulting from the weighing of the residents are only recorded in the passbook and the residents' savings cannot be taken directly. For taking citizens' savings, it can only be done once a year. When taking citizens' savings, the total amount of savings is for 1 year. In processing the bank's trash data, it is still written manually with a document filing system that is not neat and the writing is not clear, finally the data is tucked and lost. So that to find the data needed a long time, it felt less effective and inefficient. Based on the description of the above problems, a web-based garbage bank data processing application was built. This application replaces the process of recording junk data and data of residents who still use books, increase security in the information of citizens' savings, make it easier for residents to see citizens' savings, as well as help waste bank managers in managing the recording of citizens' data and knowing the history of the sale of people's waste and the total proceeds of selling garbage citizens every year.
Temporal Proximity Filtering

Users bundle the consumption of their favorite content in temporal proximity to each other, according to their preferences and tastes. Thus, the underlying attributes of items implicitly match user preferences. However, current recommender systems largely ignore this fundamental driver in identifying matching items. In this work, we introduce a novel temporal proximity filtering method to enable items-matching. First, we demonstrate that proximity preferences exist. Second, we present a temporal proximity induced similarity metric driven by user tastes, and third, we show that this induced similarity can be used to learn items pairwise similarity in attribute space. The proposed model does not rely on any knowledge outside users' consumption and provide a novel way to devise user preferences and tastes driven novel items recommender.
Analisis Perbandingan Hidrograf Satuan Sintetik Gama I dan SCS (HEC-HMS) dengan Hidrograf Satuan Terukur di Sungai Way Besai

The Way Besai River is located in Sumber Jaya District, West Lampung Regency. River discharge is an indicator of watershed function in transforming rain into stream flow. River discharge is generally presented by hydrograph. There are two methods to derive unit hydrograph, i. e. Measured Unit Hydrograph method (HST) and Synthetic Unit Hydrograph method (HSS). Synthetic Unit Hydrograph is used if the watershed does not have sufficient hydrometry data for calculating flood discharge. The purpose of this study is to analyze Synthetic Unit Hydrograph Gama I, Synthetic Unit Hydrograph SCS (HEC-HMS), and measured unit hydrograph for Way Besai River. The method used in this study includes Synthetic Unit Hydrograph Gama I, Synthetic Unit Hydrograph SCS (HEC-HMS), and Measured Unit Hydrograph. The results of this study show that Unit Hydrograph derive d from Synthetic Unit Hydrograph SCS (HEC-HMS) is better than the result derive d from Synthetic Unit Hydrograph Gama I based on peak discharge, peak time, base time and base flow values. Keywords: Watershed, Discharge, Synthetic Unit Hydrograph, Measured Hydrograph Unit, SCS (HEC-HMS), Gama I.
When does the Forename End and the Surname Begin? Saints’ Names as Compound Forenames in Spanish

While cataloging colonial-era Spanish-language materials, the investigator encountered personal names in which the forename, given in honor of a saint, includes a phrase-like qualifier such as a place name or attribute. In these situations, catalogers occasionally mistake the qualifier as part of the surname. Cataloging rules provide guidance in establishing compound surnames but not so much with forenames. For this article, 28 such forenames were searched in the Library of Congress Name Authority File to identify problematic authorized access points. Familiarity with naming customs in Spanish-speaking societies and with saints’ names is needed when creating or revising these access points.
RSL19BD at DBDC4: Ensemble of Decision Tree-based and LSTM-based Models

RSL19BD (Waseda University Sakai Laboratory) participated in the Fourth Dialogue Breakdown Detection Challenge (DBDC4) and submitted five runs to both English and Japanese subtasks. In these runs, we utilise the Decision Tree-based model and the Long Short-Term Memory-based (LSTM-based) model following the approaches of RSL17BD and KTH in the Third Dialogue Breakdown Detection Challenge (DBDC3) respectively. The Decision Tree-based model follows the approach of RSL17BD but utilises RandomForestRegressor instead of ExtraTreesRegressor. In addition, instead of predicting the mean and the variance of the probability distribution of the three breakdown labels, it predicts the probability of each label directly. The LSTM-based model follows the approach of KTH with some changes in the architecture and utilises Convolutional Neural Network (CNN) to perform text feature extraction. In addition, instead of targeting the single breakdown label and minimising the categorical cross entropy loss, it targets the probability distribution of the three breakdown labels and minimises the mean squared error. Run 1 utilises a Decision Tree-based model; Run 2 utilises an LSTM-based model; Run 3 performs an ensemble of 5 LSTM-based models; Run 4 performs an ensemble of Run 1 and Run 2; Run 5 performs an ensemble of Run 1 and Run 3. Run 5 statistically significantly outperformed all other runs in terms of MSE (NB, PB, B) for the English data and all other runs except Run 4 in terms of MSE (NB, PB, B) for the Japanese data (alpha level = 0.05).
PENGGUNAAN KALIMAT DALAM TEKS BERITA SISWA KELAS VIII B SMP PEMBANGUNAN LABORATORIUM UNP TAHUN AJARAN 2018

ABSTRACT The purpose of this study was to describe the use of sentences in the news text of class VIII B SMP Pembangunan Laboratorium UNP academic year 2018. This type of research is qualitative research with descriptive methods. The research entry is the news text writing of class VIII B students, amounting to 28 texts from 28 people. Data collection is done through documentation studies. Data were analyzed by referring to the Miles and Huberman models with steps, namely (1) doing data reduction, (2), displaying data, and (3) making conclusions and verification (conclusion drawing / verification). Based on the results of the study, the use of sentences used in the text includes single sentences and compound sentences. The use of single sentences was found 105 (57%) of 183 sentences as research data. Whereas, compound sentences were found 78 (42%) of 183 sentences as research data. The use of sentences based on single sentences is found 81 (76%) verbal predicate sentences of 105 single sentences, 8 (8%) numeral predicate sentences of 105 single sentences, 7 (7%) nominal sentences of 105 single sentences, 6 (6%) sentences the sentence has an adjunctival predicate of 105 single sentences, and 3 (3%) prepositional prediction of 105 single sentences. Then, the use of sentences based on compound sentences found 41 (53%) compound sentences equivalent from 78 compound sentences and 37 (47%) multilevel compound sentences from 78 compound sentences. Kata kunci: Teks Berita, Penggunaan Kalimat
The Contractual Cryptoeconomy: An Arrow of Time for Economics

We consider the potential blockchains have for building a framework for all manner of contracts that can characterize an economy using the unifying idea of control over their duration.Such a contractual cryptoeconomy (CCE) would accommodate a broader variety of contracts than smart contracts, which are suitable for a relatively small portion of the set of all feasible contracts.We proceed by examining the idea of a contract's natural life as a common feature shared across all contracts, be they incomplete or complete.This simplifying idea suggests why providing flexibility over a contract's duration on a blockchain -through innovations such as HTLCs -is necessary to increasing the variety of contracts that can be feasibly represented.We also assess participation in a CCE that features blockchains with differing degrees of security.We do so by focusing on how the value of a contract is related directly to its natural life for both its immediate participants and, through externalities across the CCE, to a wider set of users.A key idea provides the overall impetus: When contracts rely on third-party intermediation, at least some contractual surplus is dissipated in arbiter rent, making the quality of third-party arbitration as important as its scale.By contrast, blockchains create contractual mechanisms that act as Coasian exchanges that can internalize this arbiter rent.However, crucially, the degree to which their use requires forgoing contractual complexity and absorbing the cost of externalities can determine the relative benefits provided by a CCE.
On optimal weak algebraic manipulation detection codes and weighted external difference families

This paper provides a combinatorial characterization of weak algebraic manipulation detection (AMD) codes via a kind of generalized external difference families called bounded standard weighted external difference families (BSWEDFs). By means of this characterization, we improve a known lower bound on the maximum probability of successful tampering for the adversary's all possible strategies in weak AMD codes. We clarify the relationship between weak AMD codes and BSWEDFs with various properties. We also propose several explicit constructions for BSWEDFs, some of which can generate new optimal weak AMD codes.
한국어 교실 발화에서 나타나는 교사와 학습자의 직시 표현 사용 양상 인칭 직시·시간 직시·장소 직시를 중심으로

The purpose of this study is to examine the use of deictic expression in teachers' and learners’ language by analyzing utterance transfer data in Korean classrooms based on a theory/premise that deictic expressions help successful communication. Deixis refers to words and phrases, such as me or here, that cannot be fully understood without additional contextual information—in this case, the identity of the speaker and the speaker's location. In order to clearly understand what deictic expressions refer to, it is necessary to understand the context as well as their dictionary definition. In this paper, we examined the use of person deixis, time deixis, and place deixis. Among them, person deixis was the most frequently used at 42%. Next, time deixis was at 30%, followed by place deictic expressions at 28%. Of the person deictic expressions, ‘we’ in the first person plural form was the most used at 44%. In the time deictic expressions, 'now' was the most used at 45%, and ‘this, this one’ occupied 40% and ‘here’ at 33%, respectively. In the Korean language classroom, we could confirm the use of deictic expression through the analysis of teachers and learners’ utterance. In the future, it will be necessary to study and analyze the use of deictic expression, including discourse deixis and social deixis, and the obstacles and effectiveness in the use of deictic expression.
An Anomaly Detection Model Based on Immune Network with Variable Any-R-Intervals Matching Rule

When the immune network is used in anomalistic electromagnetism signals detection, a critical issue emerged that lots of “detection holes (gaps of the detector coverage compare to the target area)” are caused by fixed-size detectors and invariable matching threshold. This paper improves the original model by increasing the detectors’ coverage and proposes an anomalistic electromagnetism signal detection model based on an immune network with variable any-r-intervals matching rule. The sizes and matching thresholds of different detectors will learn from the training set in this model, which can reduce the detection holes obviously. The model evaluated by wireless signals and the experiment results show that the model can reduce detection holes and improve detection accuracy compared with the original model.
@bonstewart 100% agree. Have to want it. ...

@bonstewart 100% agree. Have to want it. It isn't cognitive apprenticeship it's agentive apprenticeship. With our #checkoutmydomain we. wanted to root these networks in public
Quantum information masking: deterministic versus probabilistic

We investigate quantum information masking for arbitrary dimensional quantum states. We show that mutually orthogonal quantum states can always be served for deterministic masking of quantum information. We further construct a probabilistic masking machine for linearly independent states. It is shown that a set of d dimensional states, $\{ \vert a_1 \rangle_A, \vert a_2 \rangle_A, \dots, \vert a_n \rangle_A \}$, $n \leq d$, can be probabilistically masked by a general unitary-reduction operation if they are linearly independent. The maximal successful probability of probabilistic masking is analyzed and derived for the case of two initial states.
A Survey on Enhanced RSA Algorithms

Cryptography is a field in computer science and mathematics that entails techniques of securing communication between two parties in the presence of a third party. This is achieved through the use of several methods, such as encryption, decryption, signing, generating of pseudorandom numbers, among many others. Cryptography uses a key, or some sort of a password to either encrypt or decrypt a message that needs to be kept secret. This is made possible using two classes of key-based encryption and decryption algorithms, namely symmetric and asymmetric algorithms. The best known and the most widely used public key system is RSA. This algorithm comprises of three phases, which are the key generation phase, encryption phase, and the decryption phase. Owing to the advancement in computing technology, RSA is prone to some security risks, which makes it less secure. The following paper preview different proposals on different methods used to enhance the RSA algorithm and increase its security. Some of these enhancements include combining the RSA algorithm with Diffie-Hellman or ElGamal algorithm, modification of RSA to include three or four prime numbers, offline storage of generated keys, a secured algorithm for RSA where the message can be encrypted using dual encryption keys, etc.
Live Demonstration: 4-DoF Parallax Tolerant Light Field Stitching

This demonstration shows a 4-Degree-of-Freedom (4-DoF) parallax tolerant light field (LF) stitching system to generate large field of view (FoV) LF with interactive LF experiences. It can capture the LFs in real-time, generate the large FoV LF with high visual quality and visualize the advantage of large FoV LF by interactive 3D applications like 4-DoF stereo panorama, digital refocusing and 3D point cloud reconstruction.
New Item Consumption Prediction Using Deep Learning

Recommendation systems have become ubiquitous in today's online world and are an integral part of practically every e-commerce platform. While traditional recommender systems use customer history, this approach is not feasible in 'cold start' scenarios. Such scenarios include the need to produce recommendations for new or unregistered users and the introduction of new items. In this study, we present the Purchase Intent Session-bAsed (PISA) algorithm, a content-based algorithm for predicting the purchase intent for cold start session-based scenarios. Our approach employs deep learning techniques both for modeling the content and purchase intent prediction. Our experiments show that PISA outperforms a well-known deep learning baseline when new items are introduced. In addition, while content-based approaches often fail to perform well in highly imbalanced datasets, our approach successfully handles such cases. Finally, our experiments show that combining PISA with the baseline in non-cold start scenarios further improves performance.
Analisis Plasmodium Malaria dalam Sel Darah Merah (Eritrosit) melalui Segmentasi Warna dan Deteksi Tepi Sobel

In this research, There were 9 images for training data and 26 images for test data. This image processing studied first carried out a cropping process on training data images. Then Pre-processing was also done to eliminated noise using the Salt and Pepper Noise method. After that, the RGB image results obtained were converted to grayscale images. Then the color segmentation process was based on the mean and standard deviation values. The edge detection process was then carried out using the sobel edge detection method and the results showed visible edge thickening on plasmodium. Through the color segmentation process, the percentage of plasmodium in the blood was <9%. In the process of identifying 26 test image data, 20 successful images and 6 images were declared failed to be identified. So the percentage of success of color segmentation in identification was 76.9% for 26 input data. Keywords : Sobel edge detection,color segmentation, plasmodium, image processing.
DEVELOPING ENGLISH MODULE FOR HOSPITALITY STUDENTS USING INQUIRY-BASED LANGUAGE LEARNING IN BALIKPAPAN STATE POLYTECHNIC

This research is aimed at developing the existing English module for hospitality students to fulfill the students' needs in learning English using inquiry-based language learning at Balikpapan State Polytechnic. This research was conducted in the second semester of hospitality students at Balikpapan State Polytechnic. The research methodology used in this research was a research and development (R &amp; D) for developing supplementary existing English module for hospitality students using IBLL. There are two stages of R &amp; D study: (1) exploration stage which consists of library research, document analysis, and needs analysis. The purpose of the exploration stage is to find out the weaknesses of the existing English module by conducting documents analysis and to find out the students' need towards English materials by conducting an interview and delivering questionnaire. The result of reveals as follows: (a) the students need ESP (English for Specific Purposes ) materials; (b) the contents of the existing module are too general, only focus on TOEFL preparation and do not correspond with students’ need and integrated English skills; (c) the procedure of the existing module only focus on lecturer center ; and (2) development stage which is purposed to design the supplementary existing English module through several processes: (a) designing prototype based on the result of exploration stage; (b) experts validation; (c) trying out the prototype; (d) final revision. The data was taken from expert validation form, questionnaire, focus group discussion (FGD), and classroom observation. The data was analyzed by using an interactive method. The result shows that supplementary existing English module for Hospitality student is suitable to use in higher vocational education.
Personalized Web Image Organization

Due to the problem of semantic gap, i.e. the visual content of an image may not represent its semantics well, existing efforts on web image organization usually transform this task to clusteringClustering the surrounding text. However, because the surrounding text is usually short and the wordsWord|( therein usually appear only once, existing textText clustering clusteringClustering algorithmsAlgorithm can hardly use the statistical informationStatistical information for image representationRepresentation and may achieve downgraded performancePerformance with higher computational cost caused by learning fromTag noisy tagsNoisy tags. This chapter presents using theProbabilistic fusion adaptive resonance theory Probabilistic ARTAdaptive resonance theory with userUser preference|( preferencePreference architectureArchitecture, as introduced in Sects. 3.5 and 3.4 , for personalizedPersonalized web image organization. This fused algorithmAlgorithm|( is namedProbabilistic fusion Probabilistic FusionFusion ARTProbabilistic fusion adaptive resonance theory (PF-ART), which groupsGroups images of similar semantics together and simultaneously mines the key tagsTag/topics of individual clusters. Moreover, it performsSupervised learning semi-supervised learningSemi-supervised learning using the user-provided taggingsUser-provided taggings for images to give users direct control of the generated clusters. An agglomerative merging strategy is further used to organize the clusters into a hierarchyHierarchy|(, which is of a multi-branch treeMulti-branch tree structureStructure rather than a binary treeTree|( generated by traditional hierarchicalHierarchical clustering clusteringClustering algorithms. The entire two-step algorithm is calledPersonalized Personalized HierarchicalHierarchical|( Theme-based Clustering (PHTC) Personalized hierarchical theme-based clustering , forTag tag-based web image organization. Two large-scale real-world web image collections, namely the NUS-WIDENUS-WIDE and the Flickr datasetsDataset, are used to evaluateHierarchical Theme-based Clustering (HTC)|( PHTCPersonalized hierarchical theme-based clustering and compare it with existing algorithms in terms of clusteringClustering performancePerformance and time cost. The content of this chapter is summarized and extended from the priorPrior study [17] (©2012 IEEE. Reprinted, with permission, from [17]).
A Personalized Subreddit Recommendation Engine

This paper aims to improve upon the generic recommendations that Reddit provides for its users. We propose a novel personalized recommender system that learns from both, the presence and the content of user-subreddit interaction, using implicit and explicit signals to provide robust recommendations.