Reviewerly/exHarmony huggingface dataset:
Effect of levels in Dual Tree Complex Wavelet Transform when design Universal image stego-analytic

Universal image stego-analytic has become an important issue due to the natural images features curse of dimensionality. Deep neural networks, especially deep convolution networks, have been widely used for the problem of universal image stegoanalytic design. This paper describes the effect of selecting suitable value for number of levels during image pre-processing with Dual Tree Complex Wavelet Transform. This value may significantly affect the detection accuracy which is obtained to evaluate the performance of the proposed system. The proposed system is evaluated using three content-adaptive methods, named Highly Undetetable steGO (HUGO), Wavelet Obtained Weights (WOW) and UNIversal WAvelet Relative Distortion (UNIWARD).The obtained precision 0.98387, 0.96659 and 0.98387 for the three content-adaptive methods, applied on BOSS image dataset, respectively. The obtained results show that number of level equals to 5 outperforms other numbers in terms of detection accuracy. Also it minimizes the ime required for both training and testing phases.
Design and Development of Wearable Human Activity Recognition for Healthcare Monitoring

This research deals with development of a wearable sensoring system for human activity recognition focusing on hand and leg assessments. The research attempts to sufficiently recognize the motion to provide physiotherapist about the patient condition in the remote area. The system is designed by applying Arduino as the main controller with the help of accelerometer to identify human movements and then classifying them into soft, medium and hard motions categories. From the research, data acquired from the assessment is then imported into Microsoft Excel by using Guino software to describe the human motions. The accelerometer sensors are placed as follows; the on the right hand for three positions which are on the wrist, on the elbow, and on the shoulder. Meanwhile on right leg for three position which is in tight, calf and ankle. Experimental results show that the proposed system is capable to provide reliable information to both patient and physiotherapist about the motions. The recognition for the activity is based on physiotherapist consultation which provides early descriptions of human various activities using hands and legs. The proposed system can be applied for rehabilitation and monitoring system to realize a home-based smart monitoring and assessment system.
LibGuides: Button Maker Use: Home

This guide provides instructions and related documentation for proper use of the MakerHub's button maker
2015 개정 교육과정에 따른 중학교 과학 교과서 탐구 활동에 반영된 과학과 핵심역량의 분석

The purpose of this study was to find out the implications by analyzing how science core competencies introduced in the 2015 revised national curriculum were reflected in the inquiry activities of middle school science textbooks. The results were as follows. First, The total frequency of core competencies presented in the inquiry activities of four kinds of science textbooks was 1,135 times. The frequency of core competencies in the first-grade textbooks applied to the free school year program was about 70% level compared to the second and third grades. The composition ratio was high in ‘scientific inquiry’ and ‘scientific communication’, and relatively low in ‘scientific problem solving’ and ‘scientific participation and lifelong learning’. Second, in the areas of movement and energy, matter, earth and space, the ratio of scientific inquiry ability was highest, but in the areas of life and integration, scientific communication ability was the highest. Third, the analysis of core competencies for each unit of life area showed the highest proportions of scientific communication ability in ‘biodiversity’, ‘animal and energy’, ‘stimulation and reaction’ and ‘reproduction and inheritance’ unit. On the other hand, scientific inquiry ability was the highest in ‘plant and energy’ unit. The proportion of core competencies by publishers differs, suggesting that specific agreements and guidelines for implementation after the curriculum notice need to be shared. In addition, there is a need for the plan to connect the curriculum’s goals, contents, teaching and learning methods, and evaluations with a focus on core competencies.
Library Guides: Architecture - Remote Resources: Citing Sources

This guide is designed to help architecture students and faculty access resources remotely.
LibGuides: Continuity of Library Research & Services: Virtual Research Help

This guide will help you locate and access library research and instructional support resources that are available in the event that the University is experiencing cancellation of in-person courses or a campus closure.
Retraction Note: Retraction note to: The smell of fear: on the relation between test smells and flaky tests

The authors have retracted this article Palomba and Zaidman (2019). Upon re-review of the experiment presented in the article, the authors identified errors in the flaky test detection strategy. After careful analysis of the replication study, the results presented in this article are rendered unreliable. All authors agree to this retraction.
A Latent Dirichlet Allocation and Fuzzy Clustering Based Machine Learning Model for Text Thesaurus

It is not quite possible to use manual methods to process the huge amount of structured and semi-structured data. This study aims to solve the problem of processing huge data through machine learning algorithms. We collected the text data of the company’s public opinion through crawlers, and use Latent Dirichlet Allocation (LDA) algorithm to extract the keywords of the text, and uses fuzzy clustering to cluster the keywords to form different topics. The topic keywords will be used as a seed dictionary for new word discovery. In order to verify the efficiency of machine learning in new word discovery, algorithms based on association rules, N-Gram, PMI, andWord2vec were used for comparative testing of new word discovery. The experimental results show that the Word2vec algorithm based on machine learning model has the highest accuracy, recall and F-value indicators.
Low Rate Compression of Video with Dynamic Backgrounds

We present a technique for very low rate encoding of videos with semantically salient foregrounds and dynamic background motion, such as an outdoor sports game. Our technique uses a MaskRCNN semantic segmentation neural network to separate video into foreground and background. Foreground is stored using a traditional video codec, along with a small semantic mask video which is upsampled during decoding. Missing regions of the background are filled using nearby frames, and the resulting video is stored using dynamic video motion sprites, a technique for good visual quality compression of dynamic backgrounds using static sprites, static vibration modes, and a small number of per-frame global motion parameters. By representing the backgrounds using static descriptors, our technique achieves higher visual background quality while preserving fidelity of important foreground regions. Our technique can target lower bitrates than may be appropriate for traditional codecs such as AVC and HEVC.
Brain system influences on teaching-learning process and stimuli

This research shows how the brain system influences the teaching-learning process and the stimuli that must have applied in the classroom to generate significant learning in the students, the methodology used was the bibliographic review in which some criteria have referenced. The contributions of authors, the inductive and deductive since the criteria of the cited authors have analyzed, the objective of the work was to demonstrate the incidence of the correct functioning of the brain in the educational process.
On the Influence of Interval Normalization in IVOVO Fuzzy Multi-class Classifier.

IVOVO stands for Inverval-Valued One-Vs-One and is the combination of IVTURS fuzzy classifier and the One-Vs-One strategy. This method is designed to improve the performance of IVTURS in multi-class problems, by dividing the original problem into simpler binary ones. The key issue with IVTURS is that interval-valued confidence degrees for each class are returned and, consequently, they have to be normalized for applying a One-Vs-One strategy. However, there is no consensus on which normalization method should be used with intervals. In IVOVO, the normalization method based on the upper bounds was considered as it maintains the admissible order between intervals and also the proportion of ignorance, but no further study was developed. In this work, we aim to extend this analysis considering several normalizations in the literature. We will study both their main theoretical properties and empirical performance in the final results of IVOVO.
Difficulty Classification of Mountainbike Downhill Trails Utilizing Deep Neural Networks

The difficulty of mountainbike downhill trails is a subjective perception. However, sports-associations and mountainbike park operators attempt to group trails into different levels of difficulty with scales like the Singletrail-Skala (S0-S5) or colored scales (blue, red, black, ...) as proposed by The International Mountain Bicycling Association. Inconsistencies in difficulty grading occur due to the various scales, different people grading the trails, differences in topography, and more. We propose an end-to-end deep learning approach to classify trails into three difficulties easy, medium, and hard by using sensor data. With mbientlab Meta Motion r0.2 sensor units, we record accelerometer- and gyroscope data of one rider on multiple trail segments. A 2D convolutional neural network is trained with a stacked and concatenated representation of the aforementioned data as its input. We run experiments with five different sample- and five different kernel sizes and achieve a maximum Sparse Categorical Accuracy of 0.9097. To the best of our knowledge, this is the first work targeting computational difficulty classification of mountainbike downhill trails.
Reduction of programs execution time for tasks related to sequences or matrices

The article discusses three approaches to reducing runtime of the programs, which are solutions of Olympiad tasks on computer science, related to sequences or matrices. The first approach is based on the representation of some sequences in matrix form and then the program of calculating the members of the sequence will have asymptotics equal to the time complexity of the exponentiation algorithm and will be O(log (n)). The second approach is to upgrade the known code to obtain significant reduction of the program runtime. This approach is very important to know for scientists who write code for scientific researches and are faced with matrix multiplication operations. The third approach is based on reducing time complexity by search for regularities; the author's task is presented and this approach is used to solve it.
BIBLIOGRAPHIC AND ONLINE CITATION TOOLS IN THE WORK OF STUDENTS IN HUMANITIES: SURVEY RESULTS ANALYSIS

The development of information and communication technologies (ICT) has significantly changed the perception and the way of access to information. They require the formation and development of additional skills in each individual related to competences to work with various information resources and sources and their presentation.The current text will present the results of a 2019 blitz survey among humanities students from the University of Library Studies and Information Technologies (ULSIT), whose goal is to determine the degree of use of citation generators that greatly facilitate the work of every researcher in the process of creating author texts. The research hypothesis is that, despite the relatively high level of bibliographical citation and correctness of citation, rules are often difficult for students to apply. Another working hypothesis of the study is that millennial students who have grown up with technology are making extensive use of new technologies (and specialized software) when working with bibliographic sources, including the preparation of citation lists.
Syntagmatic Modelling: Proposal for Indexical Representation of Evolutions of Notes in Patient’s Records

The aim of this paper is to propose a model indexical representation, using the syntagms referring to the names of diseases, symptoms and signs recorded in the evolution of notes in patient's record, aiming the organization and access to information of these documents with greater precision.Qualitative research based on Content Analysis (CA), was carried on having as its locus the Walter Cantidio University Hospital, Federal University of Ceará, Fortaleza, Brazil.The corpora consist of twenty evolutions of two Patient's Records, totaling eight volumes.Evolution was read and the syntagms referring to diseases, symptoms and signs were selected, and the index was organized with the mapped syntagms.Findings: 1200 syntagms referring to the names of diseases, symptoms and signs are presented according to the indexes, considering that the syntagms accurately state the particularity of the information recorded in the evolution of notes in patient's record and may contribute to the access and retrieval of information with better precision in the Medical and Statistics Archives Services (MSAS).This paper shows that the use of syntagms make possible to offer access and retrieval of information with higher added value in the context of the evolution of notes in patient's record, since they express the substance of what they name.We consider that a structured information retrieval system is highly relevant for Medical and Statistics Archives Services (MSAS).The syntagms bring contributions in understanding the planning of patient care actions and are a tool for researchers in context evaluation of the diseases treated in the health organizations.We infer that just as in any other domain of knowledge, in the context of this research, such modeling should also observe the stages of definition of the lexicon and base symbols, definition of a grammar to be adopted and definition of semantics that will at the end contribute to the construction of indexes, in this case, constituted by the syntagms.This fact is effective as a paradigm shift in the use of uniterms or concepts composed of a maximum of three lexical units for the indexical representation of health documentation, such as Patient's Records.Finally, the data from this research can be reused for other qualitative studies allowing other perceptions regarding the use of syntagms for indexical representation of MSAS and contribute to more specific evidence-based medicine studies and also to other research themes: patient speech, therapy and exams.
QUESTIONING AND ANSWERING: A LEARNING TECHNIQUE TO IMPROVE COMMUNICATION SKILL AND LEARNING OUTCOME IN THE ELEMENTERY SCHOLL

Communication skills are the ability to express ideas both verbally and non-verbally. Learning outcomes are the level of acquisition of student knowledge related to the development of competencies. Both of these can be improved in the classroom by using Questioning and Answering techniques. The purpose of the study was to improve communication skills and student learning outcomes in class IV SDN 006 Langgini. The study design used a Class Action Research (PTK) design which consists of four stages: planning, action, observation and reflection. The research subjects were 29 students in class IV SDB 006 Langgini. The instrument for measuring communication skills used observation sheets while learning outcomes were assessed by providing tests. Data were analyzed descriptively quantitatively. The results showed communication skills in first cycle was 63.22 and in second cycle amounted to 73.99 which meant an increase from first cycle to second cycle. Learning outcomes also increased by 74.21 in first cycle and 89.66 in second cycle. Thus it can be concluded that the application of techniques Questioning and Answering can improve communication skills and learning outcomes of fourth grade students of SDN 006 Langgini in semester 2019/2020.
THE ESSENCE, STRUCTURE AND CONTENT OF PREPARATION FOR THE FORMATION OF PROFESSIONAL COMPETENCE OF FUTURE EDUCATORS (ON THE MATERIAL OF THE PEDAGOGICAL PARTNERSHIP CONTENT MODULE)

the eSSence, StRuctuRe and content of pRepaRation foR the foRMation of pRofeSSionaL coMpetence of futuRe educatoRS (on the MateRiaL of the pedagogicaL paRtneRShip content ModuLe)Summary.The article substantiates the essence, peculiarities of structure and content of formation of professional competence of future educators in the issues of establishing pedagogical partnership.Educational integrated course "Pedagogy", developed on a modular system of education and includes the following content modules: "General pedagogy", "Pre-school pedagogy", "Inclusive education" and "Pedagogical partnership".The content module "Pedagogical Partnership" includes the purpose, the main tasks aimed at the formation of students of general and professional competences.The results of a mini-survey of students on the content of each module are presented; a diagnostic section of the students' professional competence was formed, which further made it necessary to develop criteria: outlook, diagnostic, content, and procedural.The levels of professional competence of students of the 2nd year of specialty "Preschool education" (high, sufficient, average low) and their indicators are characterized.Innovative methods of working with students at seminars and practical classes are highlighted: role-playing pedagogical games, analysis of problem situations from the perspective of modern interpretation, problem-seeking tasks, studying practical experience in the application in the future profession (event modeling), development of pedagogical and methodological tips and recommendations caregivers and parents; creation of necessary conditions for realization of partnership interaction; effective use of modern forms of work in partnership with parents; teachers, various social institutions.The purpose of laboratory work is revealed: to find out students' level of mastery of practical skills to determine principles and strategy of pedagogical partnership, interaction of preschool education institution with different social institutions, peculiarities of use of models of educational process for parents, to apply pedagogical partnership technologies in practice in educational establishments and institutions adults and preschoolers.
COMPARATIVE ANALYSIS OF NASH AUCTION EQUILIBRIUM MODEL AND ENERGY AWARE NASH EQUILIBRIUM MODEL FOR RESOURCE PROVISIONING IN HETEROGENEOUS CLOUD

Cloud computing is an important computing infrastructure for several applications. It offers the global network platform for executing the processes virtually across the world. In cloud, the massive amount of computing resources are dispersed over the virtual datacenter. The pools of computing resources are made available to the user based on their requirement. These resources are allocated to the cloud user for executing the tasks. Resource provisioning allocates the resources of cloud providers to a customer. A novel approach namely NAE (Nash Auction Equilibrium) model is proposed for resource provisioning in a multi-cloud environment. Nash Equilibrium is a fundamental concept as in the theory of games and the most widely used method of predicting optimal outcome of a strategic interaction. In NAE model, the ASK-BID mechanism is used to predict the initial auction payment, utilization payment and optimal cost reservation. Energy Aware Nash Auction Equilibrium (EANAE) model is proposed to enhance the resource provisioning. In EANAE model, a workflow management is used to reduce the energy consumption by finding the dependent jobs in the environment. In this paper, Comparison between Nash Auction Equilibrium Model and Energy Aware Nash Auction Equilibrium model for resource provisioning in heterogeneous cloud is discussed.
Challenges and opportunities for optical neural network (Conference Presentation)

The parallelism of optics and the miniaturization of optical components using nanophotonic structures, such as metasurfaces, present a compelling alternative to electronic implementations of convolutional neural networks. The lack of a low-power optical nonlinearity, however, requires slow and energy-inefficient conversions between the electronic and optical domains. Here, we design an architecture that utilizes a single electrical to optical conversion by designing a free-space optical frontend unit that implements the linear operations of the first layer with the subsequent layers realized electronically. Speed and power analysis of the architecture indicates that the hybrid photonic–electronic architecture outperforms a fully electronic architecture for large image sizes and kernels. We also explore the ways the nonlinearity can be implemented in optical domain, and analyze the performance of a degenerate cavity for nonlinear image processing.
Research on subject profile of stem cell based on knowledge graph

With the expansion of research fields and rapid increase of scientific literatures, knowledge structures of subjects become more and more complex. Subject profile can reveal the multi-level and multidimensional knowledge structures of subjects like user profile characterizes users. As a new knowledge organization technology, knowledge graph can be used to construct subject profile. Stem cell and regenerative medicine is the frontier of life science, and it is expected to become the third way to treat diseases after drug therapy and surgery. Based on multi-source scientific literatures and information, a domain knowledge graph of stem cell was constructed. Based on the knowledge graph, we are designing and constructing subject profile of stem cell, which is of great significance to help decision-makers and researchers to grasp the overall research of stem cell at different levels and perspectives.
THE IMPORTANCE OF DIAGNOSTICS OF PUPILS’ PRECONCEPTIONS IN EDUCATION

The paper deals with a theoretical analysis of pupils' preconceptions, their formation, modification and importance in educational process.The purpose of the paper is to explain the importance of diagnostics of pupils' preconceptions in education, which constitute the basis for meaningful learning.Preconceptions play a crucial role in constructivist education.They are formed not only in the beginning, but throughout the whole educational process.In order to teach a pupil a new term in a way he/she will understand it, we need to start from the point he/she knows from own experience and which he/she has already come across.
Research on Quality Control Method of Color Image Segmentation Based on Cloud Computing

Traditional color image segmentation quality control method image segmentation quality is low, the control effect is not good. To solve the above problems, a color image segmentation quality control method based on cloud computing is proposed. This method is composed of five steps: first, color image acquisition architecture is designed, color image storage is completed by using cloud computing, th en cloud image is used to preprocess the collected image (color quantization, color space conversion, color similarity measurement), and th en cloud computing is used for color clustering. Finally, the regions are merged and deleted to achieve color image color consistency control and realize segmentation quality control. The results show that the method can effectively control the quality of color image segmentation, and the consistency, contrast and shape parameters are improved by 0.14, 0.19 and 0.19, respectively(Abstract).