Reviewerly/exHarmony huggingface dataset:
The Effect of Story Map To Reading Comprehension of Narrative Text Ability at The X Grade of SMA Negeri 5 Padangsidimpuan

The aim of this research was to fid out whether there is any significant effect of story map to reading comprehension of narrative text ability at the X grade of SMA Negeri 5 Padangsidimpuan. The experimental research method was used to conduct this research. The population was tended to students in the grade X of SMA Negeri 5 Padangsidimpuan with 175 students. The sample was taken by using cluster sampling and it tended to the X-3 grade of SMA Negeri 5 Padangsidimpuan with 33 students. Test and observation were used to collect data. In analysis, the writer took descriptive and statistic analyzes by using t-test formula to know interpretation of data. Based on the descriptive analysis, the writer got the students got enough category in reading comprehension of narrative text ability without using story map to get comprehension with 60.00 average. Then the students enough category after using story map to get comprehension with 67.72 averages. In the statistic analysis, tcount was higher than ttable or 4.41 > 2.75. It meant the hypothesis alternative was accepted. Therefore, there was significant effect of story map toward reading comprehension of narrative text ability at the X grade of SMA Negeri 5 Padangsidimpuan
Studi Automatic Picking Waktu Tiba Gelombang P dan S dengan Menggunakan Spektogram pada Obspy Python

One of important thing in locating hypocenter process is determine P and S arrival time of the seismogram. Beside that, frequency analysis by FFT method is needed to know the character of the seismogram, like dominant frequency. For further analysis, FFT method can be a good tools in determine P and S wave arrival time in the spectogram form. This process is called automatic picking.
THE ALIGNMENT OF INNOVATION STRATEGY, ISLAMIC HRM (IHRM) PRACTICES, AND ORGANIZATIONAL PERFORMANCE: A CONTINGENCY APPROACH

The aims of this study are to test and analyze the level alignment of innovation strategy (incremental and disruptive) with Islamic HRM (IHRM) Practices on Batik MSMEs (micro small medium entreprises) in Pekalongan, especially its environmental, social, and religious performance.Pekalongan is known as Batik creative city worldwide and has a good innovation breakthrough.The sample of this study is most of the owners/managers of Batik MSMEs in Pekalongan by using purposive sampling technique.Samples are divided into two groups using mean split approach, namely MSMEs that choose the incremental innovation strategy and MSMEs that choose disruptive innovation strategy.The statistic technique is using Euclidience Distance Regression.Semantic differential scale is used as variable measurement technique.The result tested by using bivariate model fit approach shows that there is an alignment/fit between incremental innovation strategy with conservative IHRM Practices and Organizational Performance, and on the other hand there is an alignment between disruptive innovation strategy with innovative IHRM Practices and Organizational Performance.This study provides a theory implication related to the importance of having a level of alignment of innovation strategy with IHRM Practices and Organizational Innovation.The managerial implication is MSMEs should have a strategy and innovation policy aligned to the implementation of IHRM Practices in company operation so that the organizational performance can be increased.
Voice Conversion System Based on Deep Neural Networks

The paper focuses on usage of deep neural networks for converting a person’s voice to another person’s voice, analogous to a mimic. The work in this paper introduces the concept of neural networks and deploys multi-layer deep neural networks for building a framework for voice conversion. The spectral Mel-Frequency Cepstral Coefficients (MFCCs) are converted using a 10-layer deep network while fundamental frequency ( F 0 ) conversion is accomplished by logarithmic Gaussian normalized transformation. MFCCs are subjected to inverse cepstral filtering while changes in F 0 are incorporated using Pitch Synchronous OverLap Add (PSOLA) algorithm for re-synthesis. The results obtained are compared using Mel Cepstral Distortion (MCD) for objective evaluation while ABX-listening test is conducted for subjective assessment. Maximum improvement in MCD of 13.87% is obtained for female-to-male conversion while ABX-listening test indicates that female-to-male is closest to target with an agreement of 76.2%. The method achieves reasonably good performance compared to state-of-the-art using optimal resources and avoids requirement of highly complex computations.
Human Missions Analysis for Intelligent Missions Improvement

The topic of this chapter is not manned vs. robotic missions but how to integrate them for successful missions.The point of view is from that of a human observer, an ethologist, with the goal to gain further knowledge on human behavior and high technology readiness levels in the field of exploration missions.On one hand, the concept is the adaptability of men/women to be trained and on the other hand, it is the reliability of artificial intelligence systems to be incremented.The content of the chapter is: (i) ethological analysis based on numerical methods; (ii) strategy, cooperation, and adaptation; (iii) artificial intelligence and emotional intelligence; and (iv) man-rated Mars exploration demands.
Particle Filter Based Monocular Human Tracking with a 3D Cardbox Model and a Novel Deterministic Resampling Strategy

The challenge of markerless human motion tracking is the high dimensionality of the search space. Thus, efficient exploration in the search space is of great significance. In this paper, a motion capturing algorithm is proposed for upper body motion tracking. The proposed system tracks human motion based on monocular silhouette-matching, and it is built on the top of a hierarchical particle filter, within which a novel deterministic resampling strategy (DRS) is applied. The proposed system is evaluated quantitatively with the ground truth data measured by an inertial sensor system. In addition, we compare the DRS with the stratified resampling strategy (SRS). It is shown in experiments that DRS outperforms SRS with the same amount of particles. Moreover, a new 3D articulated human upper body model with the name 3D cardbox model is created and is proven to work successfully for motion tracking. Experiments show that the proposed system can robustly track upper body motion without self-occlusion. Motions towards the camera can also be well tracked.
Random Bit Generator Mechanism Based on Elliptic Curves and Secure Hash Function

Pseudorandom bit generators (PRBG) can be designed to take the advantage of some hard number theoretic problems such as the discrete logarithm problem (DLP). Such type of generators will have good randomness and unpredictability properties as it is so difficult to find an easy solution to the regarding mathematical dilemma. Hash functions in turn play a remarkable role in many cryptographic tasks to achieve various security strengths. In this paper, a pseudorandom bit generator mechanism that is based mainly on the elliptic curve discrete logarithm problem (ECDLP) and hash derivation function is proposed. The cryptographic hash functions are used in consuming applications that require various security strengths. In a good hash function, finding whatever the input that can be mapped to any pre-specified output is considered computationally infeasible. The obtained pseudorandom bits are tested with NIST statistical tests and it also could fulfill the up-to-date standards. Moreover, a $256 \times 256$ grayscale images are encrypted with the obtained pseudorandom bits following by necessary analysis of the cipher images for security prove.
Tough microbe's DNA could be a lasting archive

Artist and DNA storage pioneer says microbes could preserve a record of humanity.
Differential Evolution Algorithm with Incremental Social Learning

In this study, the differential evolution algorithm (DE), which has a very strong place among the optimization algorithms in literature, has been tried to be improved and bettered. The algorithm has been bettered by integrating incremental social learning (ISL) structure, which was applied to different optimization algorithms previously with positive feedbacks, into DE. In this betterment, DE has been initiated to search with a number of determined individuals, new individuals have been added to the population with different approaches in certain levels, the process of adding individuals has been ended at the maximum population number determined and the search has been continued with this population number until the stopping criterion has been provided. This new bettered algorithm which has been revealed as a new version of DE has been called Incremental differential evolution algorithm (IDE). Another purpose that comes into prominence in the study is to determine the best method to add individuals in ISL structure. For this purpose, five different approaches have been used in the operation of adding individuals to DE. A set of 13 unimodal and multimodal test functions defined on a 30-dimensional space have been solved with DE and IDE algorithms improved in this study. Evaluations have been made by examining the obtained numerical results, graphics and statistical analyses.
THE DIRECTIONS OF FORMATION OF MORAL QUALITIES IN THE REQUIREMENTS OF MODERN ERA

The article has been investigated the dynamics and different aspects of moral qualities of student youth. This article is focused on the research of moral qualities in various investigations, and psychological mechanism of formation of moral qualities is explained .In the result of the research, it is determined that the formation of the values bears relative character , as well as it could go in the direction of positive and negative with the effect of situative factors. It became clear to us from this study, adequate self assessment of requirements create conditions to the positive strengthening of moral qualities. As well as, the attitude of students to the teaching, non-standard approach of moral qualities to the situation could play specific role in the progress of moral qualities.
NeurIPS 2019 Disentanglement Challenge: Improved Disentanglement through Learned Aggregation of Convolutional Feature Maps

This report to our stage 2 submission to the NeurIPS 2019 disentanglement challenge presents a simple image preprocessing method for learning disentangled latent factors. We propose to train a variational autoencoder on regionally aggregated feature maps obtained from networks pretrained on the ImageNet database, utilizing the implicit inductive bias contained in those features for disentanglement. This bias can be further enhanced by explicitly fine-tuning the feature maps on auxiliary tasks useful for the challenge, such as angle, position estimation, or color classification. Our approach achieved the 2nd place in stage 2 of the challenge. Code is available at https://github.com/mseitzer/neurips2019-disentanglement-challenge.
Stochastically Differentiable Probabilistic Programs

Probabilistic programs with mixed support (both continuous and discrete latent random variables) commonly appear in many probabilistic programming systems (PPSs). However, the existence of the discrete random variables prohibits many basic gradient-based inference engines, which makes the inference procedure on such models particularly challenging. Existing PPSs either require the user to manually marginalize out the discrete variables or to perform a composing inference by running inference separately on discrete and continuous variables. The former is infeasible in most cases whereas the latter has some fundamental shortcomings. We present a novel approach to run inference efficiently and robustly in such programs using stochastic gradient Markov Chain Monte Carlo family of algorithms. We compare our stochastic gradient-based inference algorithm against conventional baselines in several important cases of probabilistic programs with mixed support, and demonstrate that it outperforms existing composing inference baselines and works almost as well as inference in marginalized versions of the programs, but with less programming effort and at a lower computation cost.
Computational super-resolution microscopy: leveraging noise model, regularization and sparsity to achieve highest resolution

We report progress in algorithm development for a computation-based super-resolution microscopy technique. Building upon previous results, we examine our recently implemented microscope system and construct alter- native processing algorithms. Based on numerical simulations results, we evaluate the performance of each algorithm and determine the one most suitable for our super-resolution microscope.
BatchLayout: A Batch-Parallel Force-Directed Graph Layout Algorithm in Shared Memory

Force-directed algorithms are widely used to generate aesthetically pleasing layouts of graphs or networks arisen in many scientific disciplines. To visualize large-scale graphs, several parallel algorithms have been discussed in the literature. However, existing parallel algorithms do not utilize memory hierarchy efficiently and often offer limited parallelism. This paper addresses these limitations with BatchLayout, an algorithm that groups vertices into minibatches and processes them in parallel. BatchLayout also employs cache blocking techniques to utilize memory hierarchy efficiently. More parallelism and improved memory accesses coupled with force approximating techniques, better initialization, and optimized learning rate make BatchLayout significantly faster than other state-of-the-art algorithms such as ForceAtlas2 and OpenOrd. The visualization quality of layouts from BatchLayout is comparable or better than similar visualization tools. All of our source code, links to datasets, results and log files are available at this https URL.
A Heuristic Proof Procedure for First-Order Logic

Inspired by the efficient proof procedures discussed in Computability logic [3],[5],[6], we describe a heuristic proof procedure for first-order logic. This is a variant of Gentzen sequent system [2] and has the following features: (a) it views sequents as games between the machine and the environment, and (b) it views proofs as a winning strategy of the machine. From this game-based viewpoint, a poweful heuristic can be extracted and a fair degree of determinism in proof search can be obtained. This article proposes a new deductive system LKg with respect to first-order logic and proves its soundness and completeness.
Post Fall Process Improvement-An Interdisciplinary Huddle Process

The Sunflower Memory Center Long-Term Care Community Living Center had seen an increase in falls. We recognized that our post-fall process was not optimally implemented or utilized, and the decision was made to explore this element to reduce our fall rates.
Hewby, William Cooke - Biographical entry - Index to the AMA archive

Hewby, William Cooke - Biographical entry - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
Gödel's Sentence Is An Adversarial Example But Unsolvable

In recent years, different types of adversarial examples from different fields have emerged endlessly, including purely natural ones without perturbations. A variety of defenses are proposed and then broken quickly. Two fundamental questions need to be asked: What's the reason for the existence of adversarial examples and are adversarial examples unsolvable? In this paper, we will show the reason for the existence of adversarial examples is there are non-isomorphic natural explanations that can all explain data set. Specifically, for two natural explanations of being true and provable, Gödel's sentence is an adversarial example but ineliminable. It can't be solved by the re-accumulation of data set or the re-improvement of learning algorithm. Finally, from the perspective of computability, we will prove the incomputability for adversarial examples, which are unrecognizable.
A Study on the Improvement of The Survey of Demand for Afterschool-Care by a joint team of related ministries

본 연구는 2014년 도입 이후 점진적인 변화의 과정을 거쳐 온 방과후돌봄 범정부 공동 수요조사에 대하여 2018년 기준으로 현황 및 문제점을 살펴보고 이에 터하여 온종일 돌봄체계의 성공적인 구축&#65381;운영을 지원하기 위한 개선 방안을 모색하고자 실시되었다. 이를 위해 관련 정책 및 문헌 분석 과정을 거쳐 조사의 연혁과 현황 등을 분석하고, 학교현장 및 교육청 관계자와 교수-연구자 등 전문가 참여 표적집단면담을 3차례 실시하여 그 논의 내용을 대상으로 텍스트 네트워크 분석과 질적 분석을 실시하였다. 연구결과로 목적의 불명확성, 내용의 복잡성, 방식의 비체계성, 결과의 낮은 신뢰성과 미온적 활용이라는 문제점을 도출할 수 있었으며, 2019년 조사를 위한 개선방안으로 조사 목적에서 불명확성의 제거, 조사 내용에서 목적과의 정합성 제고, 조사 방식에서 일원화, 결과 활용 측면에서 신뢰성 제고와 결과의 적극적 공유를 제시하였다. 또한, 조사 방식에서는 현 수요조사의 보완책으로 학교가 돌봄이 필요한 학생들을 대상으로 직접 수요를 확인하는 기제로서 소위 프로파일링의 도입을 함께 제시하였다.The purpose of this study is to examine the status and problems of ‘The Survey of Demand for Afterschool-Care by a joint team of related ministries’, which has undergone a process of gradual change since it was introduced in 2014 and to explore improvement measures to support successful establishment and operation of the All-day Care System. To this end, the history and current situation of The Survey of Demand are analyzed through the relevant policy and literature analysis process and Text network analysis and qualitative analysis were conducted for the discussion contents by conducting three targeted group interview session. The result of this study are as follows:Firstly, the problems of The Survey of Demand in 2018 were the uncertainty of the purpose, the complicated contents, the unsystematic method and, low reliability and lukewarm utilization of results. Secondly, as improvement measures for the 2019 survey, it was proposed of eliminating uncertainty from the purpose, enhancing consistency of survey content and objectives, active supplementation such as unifying the survey method, increase reliability of the results and so on. And this study proposed the introduction of so-called profiling as a mechanism for checking demand directly to students who need to be cared for by schools as a supplement to the current demand survey.
Detecting Potential Topics In News Using BERT, CRF and Wikipedia

For a news content distribution platform like Dailyhunt, Named Entity Recognition is a pivotal task for building better user recommendation and notification algorithms. Apart from identifying names, locations, organisations from the news for 13+ Indian languages and use them in algorithms, we also need to identify n-grams which do not necessarily fit in the definition of Named-Entity, yet they are important. For example, "me too movement", "beef ban", "alwar mob lynching". In this exercise, given an English language text, we are trying to detect case-less n-grams which convey important information and can be used as topics and/or hashtags for a news. Model is built using Wikipedia titles data, private English news corpus and BERT-Multilingual pre-trained model, Bi-GRU and CRF architecture. It shows promising results when compared with industry best Flair, Spacy and Stanford-caseless-NER in terms of F1 and especially Recall.
DNN-based Speech Synthesis using Dialogue-Act Information and Its Evaluation with Respect to Illocutionary Act Naturalness

This paper aims at improving naturalness of synthesized speech generated by a text-to-speech (TTS) systemwithin a spoken dialogue system with respect to “how natural the system’s intention is perceived via the synthesizedspeech”. We call this measure “illocutionary act naturalness” in this paper. To achieve this aim, we propose toutilize dialogue-act (DA) information as an auxiliary feature for a deep neural network (DNN)-based speech synthesissystem. First, we construct a speech database with DA tags. Second, we build the proposed DNN-based speechsynthesis system based on the database. Then, we evaluate the proposed method by comparing its performance withtwo conventional hidden Markov model (HMM)-based speech synthesis systems, namely, the style-mixed modelingmethod and the style adaptation method. The objective evaluation results show that the proposed method overwhelmsthe style-mixed modeling method in the accuracy of reproduction of global prosodic characteristics of dialogue-acts.They also reveal that the proposed method overwhelms the style adaptation method in the accuracy of reproduction of sentence final tone characteristics of dialogue-acts. The subjective evaluation results also show that the proposed method improves the illocutionary act naturalness compared with the two conventional methods.
INVESTIGATING PROFESSIONAL AWARENESS OF THE CORRECTIONAL PEDAGOGUE

Aim: The paper is devoted to highlighting the results of investigating the peculiarities of professional awareness of correctional pedagogues. Research methods: To achieve the goals of the investigation, business games, testing, evaluation of correctional pedagogues by the supervisor (curator, director), analysis of special documentation, activity monitoring and the method of solving professional tasks have been used. The results have been processed mathematically and accumulated in the database. They have been developed and represented in the form of tables. To determine the levels of development of professional awareness of correctional pedagogues both theoretical and empirical approaches have been used. Results: In the paper the detailed description of the developed levels of each component of professional awareness (cognitive, reflexive, axiological, motivational, affective) is presented, the main stages of the investigation work are determined: structuring of professional awareness; external evaluation of the correctional pedagogue’s activity; comparative analysis of the results of the investigation of the first and second stages of the experiment; dependencies between levels of professional awareness and different factors of professional activity development are established. The numerical results obtained during the experiment are also given. The factors of influence on the levels of development of professional awareness of correctional pedagogues are revealed: experience professional activity, working conditions, personal circumstances, awareness of issues of importance of the level of professional awareness and its components in the professional development of the employee. The results obtained during the investigation have provided the bases for developing the ways to optimize the forming professional awareness of correctional pedagogues: expanding the experience of professional activity; creating optimal professional conditions; adapting personal circumstances; disseminating the knowledge on issues of importance of level of professional awareness and its components in professional development of correctional pedagogues. Conclusions: The materials covered in the paper indicate the need: to increase the levels of development of the professional awareness of correctional pedagogues; to form the adequate professional self-esteem; to establish the dependency between professional awareness and the level of professional competence; to ensure positive impact of identified factors of professional awareness development; to form the developing technology for optimization of the process of professional awareness development in correctional pedagogues with different work experience.
Geology and Petro-chemistry of the Precambrian Rocks around Ipoti and Oke-Ila Area, Southwest Nigeria: A Preliminary Investigation for Mineral Exploration

Pollution and shortages in clean water supplies are some of the most serious problems that humanity is facing. In many Asian countries and elsewhere, the demand for potable water doubles every 10-15 years due to rising domestic consumption and the increasing needs of industry [1,2]. Eutrophication of municipal and industrial water reservoirs is a global concern and has been identified as a major environmental problem for water resource management. Furthermore, about 80 million tons of nitrogen fertilizers are applied globally per year to maximize yield [3], and no more than 40% of this amount is taken up by crops [4].