Reviewerly/exHarmony huggingface dataset:
The recurrence plot analysis in the processing of experimental biomedical data

In this article, we proposed a method for identifying the individual characteristics of motor activity based on recurrence analysis as applied to encepholography of the human brain. The analysis was carried out according to the real and imaginary (for the MEG only by imaginary) movements of the subjects and was compared with the background recording when the subject was at rest. This approach allows us to identify channels for each subject in which the frequency increases at the moment of motor activity and / or a stable pattern is formed that corresponds to this movement. The proposed method has a large number of applied applications in medicine and neurophysiology.
Automatic classification for preventing duplication of online multimedia data in secure cloud infrastructure

Cloud computing provides various types of software and hardware services collectively working together at different computational environment to the end user through internet. Cloud computing is an emerging technology that provides variety of applications to the end user and cloud services can be accessed from anywhere in the world in secured way whenever required. Nowadays free online hosting websites produce a large amount of multimedia data. It may include images, audios, 2D videos, 3D videos. Some people will use videos and audios in the distributed environment against the copyrights from the original content creators. This will create a large amount of revenue loss for the original content creator. The protection of theses multimedia content is a challenging task. Cloud computing has some security issues like authentication, privacy and data security. Our proposed system will provide highly scalable storage infrastructure in cloud environment. It also protects the multimedia content by creating a depth signature and classifying them with duplicated contents using SVM classifier. This proposed system will avoid the security issues in multimedia content and it will increase the revenue for original content creator. The proposed system can work in both public and private cloud infrastructure.
Data Mining and Clustering: A Technical Overview

The data mining is a process which is used to extract most relevant and desired information from a large data set of database and transform it into a structure required to be used and processed. Making a group of objects into classes of similar objects is called clustering. A cluster of similar data objects can be called as one group. Cluster analysis begins with making partition of the data set of available data into various groups depending on similarity of data after that labels can be assigned to those groups. This paper explains about data mining and educational data mining. This paper describes clustering and various methods or techniques of clustering. This paper also provides a brief description of K-means algorithm and its applications.
Automated Classification of Breast Cancer/Ultrasound Image Based on Non-Negative Matrix Factorization Algorithm

The topic of morphological analysis has received much attention with the increasing demands in different applications spatial in bioinformatics and biomedical applications. This paper summarizes the recent advances automated machine learning supervised suitable method for morphological Breast Cancer/masses Image Classification based on Non-Negative Matrix Factorization Algorithm. This scheme is making distinctions between all types roughly corresponding to Breast Cancer/masses types. Among many factors that morphological Classification of Breast Cancer and statistics have made great contributions for a radiologist and detection. Morphological (texture features, echogenicity, and homogenous). Breast masses analysis assists classification whether the mass is benign or malignant and finds the Breast Cancer shape. The Experimental results show that Breast Cancer images from the dataset can be classified automatically. With performance (average 94% accuracy) on a large-scale dataset, this demonstrates the strength of our method in providing an efficient tool for breast cancer multi-classification in clinical settings.
Verification and Mediating Effects of Dysfunctional Career Thinking in the Relationship between the Career Barriers and Career Maturity of University Students

본 연구는 본 연구는 대학생을 대상으로 진로장벽과 진로성숙도와의 관계에서 역기능적 진로사고가 어떠한 영향을 미치고 있는지 규명하는데 목적이 있다. 본 연구의 목적을 달성하기 위하여 SPSS 18.0과 Andrew F. Hayes(2013)가 개발한 회귀분석 연동 매크로인 ‘PROCESS Procedure’를 활용을 이용하여 빈도분석, 신뢰도분석과 상관관계분석을 실시하였고, 모형을 설정한 뒤 매개효과와 조절효과의 유의성 검증을 하였다. 이상과 같은 연구방법과 연구모형 검증을 기초로 하여 본 연구에서 도출된 결과는 다음과 같다. 가설 1은 대학생들의 진로장벽과 진로성숙도의 관계에서 역기능적 진로사고는 조절효과가 없는 것으로 나타났다. 가설 2는 첫째, 대학생들의 진로장벽은 역기능적 진로사고에 정적인 영향 미치는 것으로 나타났다. 둘째, 대학생들의 역기능적 진로사고는 진로성숙도에 부적인 영향을 미치는 것으로 나타났다. 셋째, 대학생들의 진로장벽은 진로성숙도에 부적인 영향을 미치는 것으로 나타났다. 넷째, 대학생들의 진로장벽과 진로성숙도의 관계에서 역기능적 진로사고는 매개하는 것으로 나타났다. 따라서 대학생들의 진로장벽이 높을수록 진로성숙도는 낮아지나 역기능적 진로사고 즉 진로에 대한 비합리적인 인식을 낮춰줌으로서 진로에 대한 성숙도를 높일 수 있다는 것을 시사한다.This study aims to examine the effects of dysfunctional career thinking in the relationship between university students’ career barriers and maturity. To this end, frequency, reliability, and correlation analyses were conducted using SPSS 18.0 and “PROCESS Procedure,” a regression analysis interlocking macro developed by Andrew F. Hayes (2013). A model was developed, through which the significance of any mediating and moderating effects were verified. The results of these research methods and model verifications were as follows. Regarding Hypothesis 1, the results showed that dysfunctional career thinking has no moderating effects on the relationship between university students’ career barriers and maturity. For Hypothesis 2, first, the results revealed that a career barrier has positive effects on university students’ dysfunctional career thinking. Second, university students’ dysfunctional career thinking has negative effects on their career maturity. Third, the presence of career barriers has negative effects on university students’ career maturity. Fourth, university students’ dysfunctional career thinking has a mediating effect on the relationship between career barriers and maturity. Therefore, increased career barriers lead to lower levels of career maturity but also lower the dysfunctional career thinking of university students, that is, their irrational perceptions regarding careers are decreased, implying that the level of maturity they demonstrate regarding their careers can be heightened.
Non-hamiltonian 1-tough triangulations with disjoint separating triangles

In this note, we consider triangulations of the plane. Ozeki and the second author asked whether there are non-hamiltonian 1-tough triangulations in which every two separating triangles are disjoint. We answer this question in the affirmative and strengthen a result of Nishizeki by proving that there are infinitely many non-hamiltonian 1-tough triangulations with pairwise disjoint separating triangles.
Monitoring General Education: Sociological Aspects

The scientific report presents the results of a monitoring study of the effectiveness of general education conducted by the Center for Continuing Education Economics of the RANEPA in 2013–2018. The participants of a sociological survey of the sixth monitoring wave of 2018 were 40 school principals, 2195 representatives of households, 2077 teachers of educational institutions located in urban settlements and rural areas of the Chelyabinsk region, Altai and Stavropol areas, as well as in St. Petersburg. The positions of teachers on a wide range of issues related to general education are considered: the staffing situation in schools, the quality of teaching, the requirements of families for the organization of the educational process, the satisfaction of teachers with their professional activities. Monitoring research is based on assessments of participants in educational relations and is one of the key resources for managing change in education and improving the performance of schools.
Towards a Graded Dictionary of Spanish Collocations

Several recent studies have observed that texts of different quality and written by learners at different proficiency levels also vary in the lexical combinations they contain. Such variation can be operationalized by quantitatively measuring the association between the components of these lexical combinations. In particular, pointwise mutual information (MI) has proved to be a good predictor of proficiency development, as several studies on English learners’ writing have shown. This paper examines whether association measures are also a good predictor for the proficiency level of texts written by learners of Spanish, with a view to using such information for grading lexical combinations in order to include them in a collocation dictionary of Spanish. The study also investigates whether the association measures that correlate with learners’ proficiency level can discriminate between phraseological collocations and non- collocations. Our results show that, whereas the MI of learner texts’ lexical combinations is a better predictor of author proficiency than frequency, the latter performs better in identifying phraseological collocations among the whole set of lexical combinations.
Teaching and learning English pronunciation by generating the vocal tract shapes from the frequency domain information.

This brief was based on the project AFD 05/15 SL: Teaching and Learning English Pronunciation by Generating the Vocal Tract Shapes from the Frequency Domain Information.
A Study on the Narrative Buddhist Preaching method of ‘Suttanipata’

붓다는 전도선언을 통해서 중생의 이익과 안락과 행복을 위해서 법을 설할 것을 부촉했다. 설법은 전법교화의 가장 중요한 방법이며 출가 수행자들에게 부촉된 역할이다. 하지만 포교 현장에서 스님들이 직면하는 가장 어려운 문제가 바로 설법이다. 본고는 이러한 문제인식을 바탕으로 설법방법론의 하나로 내러티브 방법을 제안하고자 했다. 내러티브 설법이란 문학성을 가미한 이야기체로 설법을 구성하는 것을 의미한다. 내러티브 설법을 활용하는 이유는 단순히 부처님의 가르침을 평면적으로 전하기보다는 청법 대중이 쉽게 알아듣고 기억할 수 있는 이야기체가 설법의 효과성을 높일 수 있기 때문이다. 『숫타니파타』는 다양한 수사법과 마지막 구절을 계속 반복해 메시지를 전하는 결구 반복법을 활용하고 있다. 『숫타니파타』는 각각의 스토리와 분명한 메시지를 가지는 경들이 많아 내러티브 설법에 적당한 경전이다. 본고에서는 내러티브 설법이 이루어지기 위한 요소들과, 직접적으로 『숫타니파타』의 경들을 소재로 내러티브 설법을 방안들을 제안했다.Through the declaration of propaganda, Buddha entrusted them with delivering sermons for public benefit, comfort and happiness. Sermon is the most important method of transmission of enlightenment and is a role entrusted to the renunciated ascetics. However, the most difficult problem faced by monks in the field is the sermon. Based on the recognition of this problem, this study tried to use the narrative method as one of the methods of sermon. narrative sermon means composing a sermon with a narrative style added with a literary character. The reason for using the narrative sermon is that rather than delivering the teachings of the Buddha monotonically, the narrative for the audience to be easily able to understand and remember can enhance the efficacy of the narrative. The Suttanipata contains a variety of rhetorical methods that can be called treasury of rhetoric. And epistrophe that conveys the message while repeating the last phrase is widely used. “Suttanipata” is a scripture suitable for narrative preaching because there are many scriptures with separate stories and clear messages. Therefore, this thesis suggested the elements for the narrative preaching and the methods of the narrative preaching directly from the works of “Suttanipata”.
Combining the APIs: Building a Chatbot

Over the course of the last few chapters, we’ve explored the Speech API in detail and used it to set up some basic examples of speech capabilities. This is only the start though – there is so much more we can do! Making use of the APIs opens up a host of innovative ideas for us to explore, and that’s before we even personalize the functionality we offer to customers.
Project: Building Alexa

For some of you, I’ll bet that is an all too common a phrase in your household – I suspect it’s a case of not if, but how many!
Improved faster R-CNN identification method for containers

In a complex port environment, the fast and effective automatic visual recognition of containers is an important part of the intelligent operation and management of ports. Due to the large amount of container image data of complex scale and shape, the traditional target detection and recognition algorithm is limited by the illumination, weather and scenes of the port, it has created challenges and difficulties in port container recognition and identification. This paper proposes a deep learning method for container target recognition detection based on the Faster R-CNN framework, the deep separable network structure is introduced into the VGG network, and the DS-VGG network is designed to improve the accuracy while reducing the network parameters to improve the recognition speed, by introducing the adversarial spatial transformer network (ASTN) to the Faster R-CNN network training to enhance the diversity of data features and improve recognition performance. In order to enhance the convolution feature extraction of container targets, a strategy training network that enhances sample target foreground features, multi-scale training learning and data amplification are used. Finally, the performance test and comparison test of the improved model proposed in this paper are carried out. The test results show that the target recognition speed is 50 frames/s on the container test set, the average accuracy rate is 97.7% and the recall rate is 94.45%. Compared with Faster R-CNN, the recognition performance is significantly improved in complex scenes such as fog, rain and night.
Automatic Rule Extraction from Access Rules Using Genetic Programming

The security policy rules in companies are generally proposed by the Chief Security Officer (CSO), who must, for instance, select by hand which access events are allowed and which ones should be forbidden. In this work we propose a way to automatically obtain rules that generalise these single-event based rules using Genetic Programming (GP), which, besides, should be able to present them in an understandable way. Our GP-based system obtains good dataset coverage and small ratios of false positives and negatives in the simulation results over real data, after testing different fitness functions and configurations in the way of coding the individuals.
Wide-sense Stationary Stochastic Processes

Wide-sense stationary stochastic processes are of interest in signal analysis and processing, as well as in physics. Their study rests on Bochner’s representation of characteristic functions, which immediately leads to the fundamental notion of power spectral measure, and on the Doob–Wiener integral that permits a mathematical definition of white noise as well as the obtention of a spectral decomposition of the trajectories of such stochastic processes, the Cram´er–Khinchin decomposition, a fundamental result with importance consequences in signal processing.
Head gimbal assembly automated visual inspection by using digital image processing

Abstract This paper presented an approach of Digital Image Processing (DIP) and measurement properties of image region for inspecting the part in Head Gimbal Assembly (HGA) process. Current, the inspection process is performed by the skilled employee, which depends on employee experiences. The inspection method proposed by using digital image processing to do an image enhancement in order to detect the abnormalities and defects on part. The measurement properties of image region is proposed to identify the abnormality occurred on HGA part after image enhancement, in production process. This research aimed to develop the algorithm to inspected HGA part by considered the number of pads, convex area value, and eccentricity value. Then used measurement properties of image region to enhance the algorithm for classifying part in production process. This approach has been developed and proved with the real part in HGA production process. It’s proved that the algorithm and method proposed can be classified the part in HGA production process.
Towards the Automatic Construction of a Multilingual Dictionary of Collocations using Distributional Semantics

This paper presents the method used to create a multilingual online dictionary of collocations of English, Portuguese, and Spanish. This resource is built automatically and contains three types of collocations: verb–object (e.g., “[to] issue [an] invoice”), adjective–noun (“deep shame”), and nominal compounds (“cigarette packet”). We take advantage of dependency parsing and statistical association measures to compile collocations of each language, and then we align them with their equivalents in the other languages by means of compositional methods which use cross-lingual models of distributional semantics. Collocations are extracted from large and assorted corpora, and the cross-lingual models are mapped using unsupervised approaches. For each collocation in a given language, the system shows different equivalents in the other languages, ranked by a confidence value. Besides the multilingual perspective, the resulting dictionary can also serve as a monolingual resource to retrieve the collocates of a given base, thus being a useful application to both native speakers and language learners. The dictionary will be published as an online tool, and all the resources generated in this research will be freely available.
Porting a Crowd-Sourced German Lexical Semantics Resource to Ontolex-Lemon

In this paper we present our work consisting of mapping the recently created open source German lexical semantics resource “Open-de-WordNet” (OdeNet) into the OntoLex-Lemon format. OdeNet was originally created in order to be integrated in the Open Multilingual Wordnet initiative. One motivation for porting OdeNet to OntoLex-Lemon is to publish in the Linguistic Linked Open Data cloud this new WordNet-compliant resource for German. At the same time we can with the help of OntoLex-Lemon link the lemmas of OdeNet to full lexical descriptions and so extend the linguistic coverage of this new WordNet resource, as we did for French, Italian and Spanish wordnets included in the Open Multilingual Wordnet collection. As a side effect, the porting of OdeNet to OntoLex-Lemon helped in discovering some issues in the original data.
Kernel Based Artificial Neural Network Technique to Enhance the Performance and Accuracy of On-Line Signature Recognition

Signature recognition is a standout amongst the most essential biometrics verification strategies, is an indispensable piece of current business exercises, and is considered a noninvasive and non-undermining process. For online signature recognition, many techniques had been presented before. Nevertheless, accuracy of the recognition system is further to be improved and also equal error rate is further to be reduced. To solve these problems, a novel classification technique has to be proposed. In this paper, Kernel Based Artificial Neural Network (KANN) is presented for online signature recognition. For experimental analysis, two datasets are utilized that are ICDAR Deutsche and ACT college dataset. The proposed K-ANN classification method gives lower performance in terms of accuracy value with 66% TPR, 73% FPR in ACT and 50% TPR, 56% FPR in ICDAR datasets respectively.
The Level of Organizational Learning for Emergency Preparedness Work on Organizational Immersion in Local Governments

이 연구의 목적은 지방자치단체의 비상대비업무 관련 학습조직화 수준과 팀원의 자기주도학습 능력 및 조직몰입 사이의 영향력 관계를 분석하였다. 이를 토대로 지방자치단체의 비상대비업무 관련 학습조직화 수준과 자기주도학습을 능동적으로 지향시키고 이를 통해 조직몰입도를 높힐 수 있도록 제언하고자 한다. 연구대상은 12개 시·도 민방위 비상대비팀 구성원 175명을 대상으로 설문조사를 실시하였다. 결과는 다음과 같다. 첫째, 비상대비 업무조직의 학습조직화와 자기주도학습, 조직몰입변인 간에는 모두 유의한 상관관계가 나타났다. 둘째, 학습조직화가 구축되면 구성원의 자기주도학습이 정적인 영향을 미치며, 직무몰입에도 긍정적 효과를 보인다. 셋째, 자기주도학습은 학습조직화와 결과변수인 조직몰입과의 매개역할을 하는 것으로 나타났다. 이에따른 본 연구의 시사점 및 한계점이 논의되었다.The purpose of the study is to analyze the relationship between the level of organizational learning related to emergency preparedness of local governments and their members’ self-directed learning ability and organizational immersion. The study was conducted by carrying out a survey of 175 members of the Civil Defense Emergency Preparedness Team in 12 cities and provinces in South Korea. The results are as follows. First, there was a significant correlation among organizational learning, self-directed learning, and organizational immersion of the emergency preparedness organizations. Second, organizational learning had a positive effect on self-directed learning and job immersion of their members. Third, self-directed learning was shown to serve as a mediator between organizational learning and organizational immersion. Findings and limitations are discussed.
Perencanaan Strategis Sistem Informasi dengan Metode Enterprise Architecture Planning (Studi Kasus: STMIK Syaikh Zainuddin NW Anjani-Lombok)

INTISARIPerkembangan dari teknologi dan sistem informasi ini menyebabkan perubahan- perubahan peran dari efisiensi dan efektivitas menjadi peran strategik. Sekarang peran sistem informasi tidak hanya untuk efisiensi dan efektivitas melainkan juga peran strategik untuk menenangkan persaingan. Persaingan yang semakin kompetitif dan ketat didalam dunia Pendidikan ini terutama tingkat perguruan tinggi yang dikelola oleh swadaya masayarakat (swasta), mengha-ruskan dan menuntut pihak pengelola untuk terus mengembangkan atau membangun sistem informasi dalam membantu aktivitas bisnis untuk mencapai tujuan dari organisasi dan sebagai layanan bagi stakeholder.Enterprise merupakan sekumpulan organisasi yang memiliki beberapa tujuan/prinsip umum dan atau suatu garisan dasar. Perguruan tinggi merupakan salah satu enterprise yang bergerak pada bidang Pendidikan. Meningkatnya kebutuhan terhadap data dan informasi dalam fungsi bisnis yang dijalankan oleh suatu perguruan tinggi merupakan salah satu pendorong pemanfaatan sistem informasi di dalam perguruan tinggi. Oleh karena itu, dalam penelitian ini akan dilakukan perancangan terhadap 3 (tiga) model arsitektur, yaitu ar-sitektur data, arsitektur, aplikasi dan arsite-ktur teknologi dengan menggunakan metode Enterprise Architecture Planning (EAP).Kata kunci— Sistem Informasi, Enterprise Architecture Planning, Arsitektur data, Arsitektur aplikasi, Arsitektur teknologi, raodmap implementasi. ABSTRACTThe development of technology and information systems has caused role changes from efficiency and effectiveness to strategic roles. Now the role of information systems is not only for efficiency and effectiveness but also a strategic role to calm competition. Competition is increasingly competitive and tight in the world of education, especially the level of higher education which is managed by self-help community (private), requires and requires the management to continue to develop or build information systems in helping business activities to achieve the goals of the organization and as a service for stakeholders.Enterprise is a group of organizations that have several general goals / principles and or a basic outline. Higher education is one of the enterprises engaged in the field of Education. The increasing need for data and information in the business functions carried out by a university is one of the drivers of the utilization of information systems in universities. Therefore, in this study there will be a design of 3 (three) architectural models, namely architectural data, architecture, applications and technology architecture using the Enterprise Architecture Planning (EAP) method. Kata kunci— Information Systems, Enterprise Architecture Planning, Data Architecture, Application Architecture, Technology Architecture, raodmap implementation.