Reviewerly/exHarmony huggingface dataset:
The DipInfoUniTo Realizer at SRST’19: Learning to Rank and Deep Morphology Prediction for Multilingual Surface Realization

We describe the system presented at the SR'19 shared task by the DipInfoUnito team.Our approach is based on supervised machine learning.In particular, we divide the SR task into two independent subtasks, namely word order prediction and morphology inflection prediction.Two neural networks with different architectures run on the same input structure, each producing a partial output which is recombined in the final step in order to produce the predicted surface form.This work is a direct successor of the architecture presented at SR'19.
A survey of Emerging Techniques in Detecting SMS Spam

In the past years, spammers have focused their attention on sending spam through short messages services (SMS) to mobile users. They have had some success because of the lack of appropriate tools to deal with this issue. This paper is dedicated to review and study the relative strengths of various emerging technologies to detect spam messages sent to mobile devices. Machine Learning methods and topic modelling techniques have been remarkably effective in classifying spam SMS. Detecting SMS spam suffers from a lack of the availability of SMS dataset and a few numbers of features in SMS. Various features extracted and dataset used by the researchers with some related issues also discussed. The most important measurements used by the researchers to evaluate the performance of these techniques were based on their recall, precision, accuracies and CAP Curve. In this review, the performance achieved by machine learning algorithms was compared, and we found that Naive Bayes and SVM produce effective performance.
Development of sEMG-based robust oral motion classification method and its application to electric wheelchair operation

Interfaces based on surface electromyography (sEMG) signals are one of the important methods for non-invasively extracting the intention of a severely disabled person and supporting environmental control of wheelchairs and personal computers. However, sEMG-based interfaces generally have a common and maximum disadvantage of vulnerability to changes in electrode position. In this study, we aimed to develop a robust oral motion classification method that is robust to change in electrode position. Five healthy adult male subjects participated in this experiment. sEMG signals of the suprahyoid muscles during five oral motions (right, left, up tongue motion, jaw opening, and clenching) were measured using a boomerang-shaped 22-channel electrode adhered to the underside of the jaw. Oral motion classification from sEMG signals was performed using a support vector machine (SVM). When sEMG signals measured at a position different from the 22-channnel electrode position where the training data for SVM classifier was obtained were used as the test data, the classification accuracy of five oral motions sharply decreased from 92.0% to 72.8%. In contrast, when the 10 trials of sEMG signals obtained in advance at different electrode positions on different days were used as training data, the robustness against electrode position change was improved drastically and the mean classification accuracy of all subjects reached 90.4%. Furthermore, we developed an electric wheelchair control system that can operate based on classified motions and verified its usefulness for wheelchair operability and driving performance thorough the experiment. The results showed that the proposed method can omit the SVM training process required every time after the electrode is attached and can operate the wheelchair immediately after electrode attachment. Such advancement of interfaces eliminates the annoyance caused to the user who uses the interface on a daily basis and is expected to lead to an improvement in the quality of life.
High-speed 3D measurements at 20,000Hz with deep convolutional neural networks

Nowadays, the speed of ultra-fast photography can exceed one quadrillion. However, it can record only two-dimensional images which lack the depth information, greatly limiting our ability to perceive and to understand the complex real-world objects. Inspired by recent successes of deep learning methods in computer vision, we present a novel high-speed three-dimensional (3D) surface imaging approach named micro deep learning profilometry (<i>&mu;</i>DLP) using the structured light illumination. With a properly trained deep neural network, the phase information is predicted from a single fringe image and then can be converted into the 3D shape. Our experiments demonstrate that <i>&mu;</i>DLP can faithfully retrieve the geometry of dynamic objects at 20,000 frames per second. Moreover, comparative results show that <i>&mu;</i>DLP has superior performance in terms of the phase accuracy, reconstruction efficiency, and the ease of implementation over widely used Fourier-transform-based fast 3D imaging techniques, verifying that <i>&mu;</i>DLP is a powerful high-speed 3D surface imaging approach.
Author identification for Under-Resourced language (KadazanDusun)

&lt;span&gt;This paper presents the task of Author Identification for KadazanDusun language by using tweets as the source of data to perform Author Identification task of short text on KadazanDusun, which is considered as one the under-resourced language in Malaysia. The aim of this paper is to demonstrate Author Identification of short text on KadazanDusun. Besides, this paper also examines the performance of two machine learning algorithms on the KadazanDusun data set by analyzing the stylometric features. Stylometric features are used to quantify the writing styles of the authors which includes character n-grams and word n-grams. The workflow of Author Identification implements the machine learning approach to solve the single-labelled multi-class problem and predict the author of a given message in KadazanDusun. Two classifiers are used to compare the accuracy including Naïve Bayes and Support Vector Machine (SVM). The results show that the combination of n-grams which is word-level unigram and {1-5}-grams with character 3-grams are the most relevant stylometric features in identifying the author of KadazanDusun message with an accuracy of 80.17%. The results also show that SVM classifier has outperformed Naive Bayes in this Author Identification task with the accuracy of 80.17%.&lt;/span&gt;
Design of an Efficient Steganography Model using Lifting based DWT and Modified-LSB Method on FPGA

The data transmission with information hiding is a challenging task in today world. To protect the secret data or image from attackers, the steganography techniques are essential. The steganography is a process of hiding the information from one channel to another in data communication. In this research work, Design of an Efficient Steganography Model using Lifting Based DWT and Modified-LSB Method on FPGA is proposed. The stegano module includes DWT (Discrete Wavelet Transformation) with lifting scheme for the cover image and encryption with Bit mapping for a secret image, an embedded module using Modified Least Significant Bit (MLSB) Method, and Inverse DWT to generate the stegano image. The recovery module includes DWT, decoding module with pixel extraction and bit retrievals, and decryption to generate the recovered secret image. The steganography model is designed using Verilog-HDL on Xilinx platform and implemented with Artix-7 Field Programmable Gate Array (FPGA). The hardware resource constraints like Area, time, and power utilization of the proposed model results are tabulated. The performance analysis of the work is evaluated using Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) Ratio for a different cover and secret images with better quality. The proposed steganography model operates at high speed, which improves communication performance.
The Development of the 2013 Student Curriculum Book Based on Thinking Actively in Social Context for Elementary School Students

This research was motivated by the necessity of having student books that suit to the 2013 curriculum objectives, the characteristics of elementary school students and the characteristics of learning outcomes. The study aims to develop valid, practical, and effective elementary school student books based on thinking actively in social context. Employing a 4-D research model (define, design, development and disseminate), the data were garnered using tests, questionnaires, observations, interviews and documentation. The data from tests and questionnaires were analyzed using descriptive statistics whereas the triangulation was used to analyze the data collected through observations, interviews, and documentation. The results showed that the developed student books met the valid criteria with a final score of 85.25% (very valid). It was found that the student books are easy to use, time-saving, and useful to implement in the classroom practices. It could also enhance student learning outcomes in terms of spiritual attitudes, social, knowledge and skills with a percentage increase of 15.35%. As those books are valid, practical, and effective; they can be used as a reference for the learning activities in elementary schools. Keywords : s tudent b ook s , 2013 curriculum, TASC, elementary school s . Abstrak Penelitian ini dilatarbelakangi oleh perlunya buku siswa yang selaras dengan tujuan kurikulum 2013, karakteristik siswa sekolah dasar, dan karakteristik hasil belajar. Penelitian ini bertujuan untuk mengembangkan buku siswa kurikulum 2013 berbasis thinking actively in social context untuk sekolah dasar yang valid, praktis, dan efektif. Menggunakan model penelitian 4-D ( define, design, development , disseminate ), data dikumpulkan mealui tes, angket, observasi, wawancara dan dokumentasi. Data yang diperoleh dari tes dan angket dianalisis menggunakan statistik deskriptif sedangkan triangulasi digunakan untuk menganalisis data yang berasal dari observasi, wawancara, dan dokumentasi. Hasil penelitian menunjukkan bahwa buku siswa yang dikembangkan telah memenuhi kriteria valid dengan skor akhir 85,25% (sangat valid). Buku siswa mudah digunakan, menghemat waktu, dan bermanfaat dalam implementasinya pada pembelajaran di kelas. Buku siswa juga dapat meningkatkan hasil belajar siswa sekolah dasar pada aspek sikap spiritual, sosial, pengetahuan dan keterampilan dengan persentase kenaikan sebesar 15,35%. Karena buku yang telah dikembangkan valid, praktis, dan efektif, buku siswa tersebut dapat dijadikan sebagai rujukan untuk kegiatan pembelajaran di sekolah dasar. Kata kunci: buku siswa, kurikulum 2013, TASC, sekolah dasar.
RACAI’s System at PharmaCoNER 2019

This paper describes the Named Entity Recognition system of the Institute for Artificial Intelligence "Mihai Drȃgȃnescu" of the Romanian Academy (RACAI for short).Our best F1 score of 0.84984 was achieved using an ensemble of two systems: a gazetteer-based baseline and a RNN-based NER system, developed specially for PharmaCoNER 2019.We will describe the individual systems and the ensemble algorithm, compare the final system to the current state of the art, as well as discuss our results with respect to the quality of the training data and its annotation strategy.The resulting NER system is language independent, provided that language-dependent resources and preprocessing tools exist, such as tokenizers and POS taggers.
SELF ESTEEM, SELF EFFICACY DAN PRESTASI AKADEMIK MAHASISWA AKUNTANSI: STUDI PADA KELAS PENGAUDITAN

This study aims to provide empirical evidence of the related between self esteem and self efficacy with academic performance on auditing course. By using non-probability sampling techniques that is purposive sampling, this research using a sample of 194 university students in Yogyakarta that take on auditing course. This research model was developed based on previous research models by using survey in data collection process. Analysis uses structural equation models by using smartPLS software. Results of this research shown the support of 2 out of 3 proposed hypothesis, namely that there is a significant positive relationship between self esteem against self efficacy and academic performance. Meanwhile, this research can not proves that self efficacy strengthen academic performance on auditing course.
A new digital signature scheme with message recovery using hybrid problems

We present a new digital signature scheme with message recovery and its authenticated encryption based on elliptic curve discrete logarithm and quadratic residue. The main idea is to provide a higher level of security than all other techniques that use signatures with single hard problem including factoring, discrete logarithm, residuosity, or elliptic curves. The proposed digital signature schemes do not involve any modular exponentiation operations that leave no gap for attackers. The security analysis demonstrates the improved performance of the proposed schemes in comparison with existing techniques in terms of the ability to resist the most common attacks
Hedges and boosters in medical and engineering research articles: A comparative corpus-based study

This study aimed to compare the use of hedges and boosters in medical sciences and engineering research articles. To fulfil this objective, the researcher provided 30 medical and 30 engineering research articles to identify the hedging and boosting devices used in them. The research articles were analysed according to lexical devices classification, focusing on hedges and boosters. The AntConc concordance software was used to identify the instances of hedges and boosters in both disciplines. Frequency, percentage and the Chi-square test were run to analyse the data. The results indicated that the difference between the frequency of hedges and boosters in medical sciences and engineering research articles was significant and meaningful. Moreover, the outcomes indicated that the most frequent hedges were epistemic modality verbs, quantifiers and nouns and the most frequent boosters were nouns, lexical verbs, modal verbs and adjectives. These discoveries of this paper may have some implications for the teaching of academic writing, especially to EFL learners.&#x0D; Keywords: Boosters, engineering research articles, hedges, medical research articles
Deep Eyes: Binocular Depth-from-Focus on Focal Stack Pairs

Human visual system relies on both binocular stereo cues and monocular focusness cues to gain effective 3D perception. In computer vision, the two problems are traditionally solved in separate tracks. In this paper, we present a unified learning-based technique that simultaneously uses both types of cues for depth inference. Specifically, we use a pair of focal stacks as input to emulate human perception. We first construct a comprehensive focal stack training dataset synthesized by depth-guided light field rendering. We then construct three individual networks: a Focus-Net to extract depth from a single focal stack, a EDoF-Net to obtain the extended depth of field (EDoF) image from the focal stack, and a Stereo-Net to conduct stereo matching. We show how to integrate them into a unified BDfF-Net to obtain high-quality depth maps. Comprehensive experiments show that our approach outperforms the state-of-the-art in both accuracy and speed and effectively emulates human vision systems.
Dependable estimations for education quality using fuzzy logic based strategy a case study (University of Kufa)

&lt;span&gt;The consideration that the Iraqi community has concentrated on the training area has delivered another college responsibility routed to superiority viewpoints for all training connected facilities. In truth, a superiority arranged facility necessitates perfection in the structure and arranging of facility exercises, in addition to amid its conveying for the received facility execution assessment strategy. In any case, considering that facility execution assessments are profoundly founded on partners’ decisions, they can be described by conceivable vulnerabilities identified with deficiency for incomplete obliviousness, imprecision for subjectivity and even dubiousness. In this way, underneath these circumstances, temperamental outcomes can be acquired by broadly measured facility investigation strategies. This paper is a strategy dependent an ongoing augmentation of ServQual display and it utilizes a consolidated way of Fuzzy Set Theory of command process technique that is proposed to adequately deal with vulnerability in facility execution examinations. Specifically, Fuzzy Set Theory is measured to manage vulnerability, while AHP strategy is embraced as device to appraise the significance loads of key facility characteristics. In this way, the key investigation of the facility esteem tree identified with the program in University of Kufa is made by using the planned strategy. The completed facility examination permits the most impacting facility execution components to be caught and remarked. At last, acquired outcomes demonstrate that the teachers' view of facility quality definitively impacts by large facility execution level. &lt;/span&gt;
Construction of New Matrix-Product Codes and Their Applications

In this paper, from special code chains <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {C}_{1} \supseteq \mathcal {C}_{2}~\supseteq \mathcal {C}_{3}$ </tex-math></inline-formula> such that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {C}^{\bot _{h}}_{1}\subseteq \mathcal {C}_{3}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {C}^{\bot _{h}}_{2}\subseteq \mathcal {C}_{2}$ </tex-math></inline-formula> , some Hermitian dual-containing (HDC) matrix-product (MP) codes are presented, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {C}_{3}$ </tex-math></inline-formula> is not HDC. By studying some constacyclic codes of lengths <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n=q^{2}\pm 1$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n=\frac {q^{2}-1}{2}$ </tex-math></inline-formula> , we construct many HDC MP codes of length <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3n$ </tex-math></inline-formula> . Consequently, many <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> -ary quantum codes with larger designed distance <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d\geq q+1$ </tex-math></inline-formula> are obtained from these MP codes, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4\leq q\leq 9$ </tex-math></inline-formula> .
Correction to: Handling Complex Meta-analytic Data Structures Using Robust Variance Estimates: a Tutorial in R

The original publication of this article contained the wrong image in Figure 1. The correct Figure 1 is presented at the next page.
Towards Understanding of Medical Randomized Controlled Trials by Conclusion Generation

Randomized controlled trials (RCTs) represent the paramount evidence of clinical medicine.Using machines to interpret the massive amount of RCTs has the potential of aiding clinical decision-making.We propose a RCT conclusion generation task from the PubMed 200k RCT sentence classification dataset to examine the effectiveness of sequence-to-sequence models on understanding RCTs.We first build a pointergenerator baseline model for conclusion generation.Then we fine-tune the state-of-the-art GPT-2 language model, which is pre-trained with general domain data, for this new medical domain task.Both automatic and human evaluation show that our GPT-2 fine-tuned models achieve improved quality and correctness in the generated conclusions compared to the baseline pointer-generator model.Further inspection points out the limitations of this current approach and future directions to explore * .
Samvaadhana : A Telugu Dialogue System in Hospital Domain

In this paper, a dialogue system for Hospital domain in Telugu, which is a resource-poor Dravidian language, has been built.It handles various hospital and doctor related queries.The main aim of this paper is to present an approach for modelling a dialogue system in a resource-poor language by combining linguistic and domain knowledge.Focusing on the question answering aspect of the dialogue system, we identified Question Classification and Query Processing as the two most important parts of the dialogue system.Our method combines deep learning techniques for question classification and computational rule-based analysis for query processing.Human evaluation of the system has been performed as there is no automated evaluation tool for dialogue systems in Telugu.Our system achieves a high overall rating along with a significantly accurate context-capturing method as shown in the results.
The Impact of Human Resources Information Systems on Human Resources Selection and Recruitment Strategy: An applied study on Arab Potash Company in the Hashemite Kingdom of Jordan

The aim of this study was to identify the impact of human resources information systems on the selection and recruitment strategy in the Potash Company. to achieve these objectives a questionnaire was developed to collect data and the statistical package for social sciences (SPSS.16.) was used to analyze the study data.A number of results were highlighted The level of importance of human resources information systems (efficiency of human resources information system, integration with other management information systems) in the company according to respondents' perceptions was moderate.In addition to the impact of this dimension in HR selection and recruitment strategy, HRIS explained (58.3%) of the variation in the strategy of selection and recruitment of human resources in the Arab Potash Company.Based on the results that the study reached, it shed light many recommendations, the most important of which is the design of website for the Arab Potash Company, which is easy to use and uncomplicated so that individuals who wish to work in these companies can apply electronically, which provides the company with the opportunity to attract as many as possible applicants who have high competencies.