Reviewerly/exHarmony huggingface dataset:
Visualizing big data via a mixture of PARAMAP and Isomap

Dimension reduction strives to represent higher dimensional data by a lower-dimensional structure. A famous approach by Carroll called Parametric Mapping or PARAMAP (Shepard &amp; Carroll, 1966) works by iterative minimization of a loss function measuring the smoothness or continuity of the mapping from the lower dimensional representation to the original data. The algorithm was revitalized with essential modifications (Akkucuk &amp; Carroll, 2006). Even though the algorithm was modified, it still needed to make a large number of randomly generated starts. In this paper we discuss the use of a variant of the Isomap method (Tenenbaum et al., 2000) to obtain a starting framework to replace the random starts. The core set of landmark points are selected by a special procedure akin to selection of seeds for the k-means algorithm. These core set of landmark points are used to create a rational start for running the PARAMAP algorithm only once but effectively reach a global minimum. Since Isomap is faster and less inclined to local optimum problems than PARAMAP, and the iterative process involved in adding new points to the configuration will be less time consuming (since only one starting configuration is used), we believe the resulting method should be better suited to deal with large data sets, and more prone to obtain an acceptable solution in realistic time.
#Você: uma revisão de literatura sobre selfies e personalidade

EnglishSelfies are photos taken alone or with others and shared on social media, nowadays they have surpassed the function of just being a way to record moments and have become a form of communication. Considering this importance in the current culture, the objective of this study was to understand the relations between selfies and personality, using a literature review. In the research, were considered articles made in the last 10 years, written on english and portuguese and indexed in the databases ScienceDirect, Scielo, Pepsic, Lilacs and BVS. Seven articles were located from the established criteria. The results indicated a constant positive association between narcissism and several individual self-posture behaviors, while the Big Five personality factors appeared to be more related to social behaviors in this activity. From what is observed, it is demonstrated the importance of developing research on the subject in the Brazilian context. portuguesAs selfies sao fotos tiradas sozinho ou com outros e compartilhadas nas redes sociais, e atualmente superaram a funcao de apenas ser um registro de momentos e passaram a ser uma forma de comunicacao. Considerando essa importância na cultura atual, o objetivo deste estudo foi compreender as relacoes entre selfies e personalidade, atraves de uma revisao de literatura. Foram considerados estudos em ingles e portugues publicados nos ultimos 10 anos nas bases de dados ScienceDirect, Scielo, Pepsic, Lilacs e BVS, sendo localizados a partir dos criterios estabelecidos um total de 7 artigos (todos em ingles). Os resultados indicaram uma constante associacao positiva entre o narcisismo e diversos comportamentos individuais de postagem de selfies, enquanto os cinco grandes fatores de personalidade pareceram estar mais relacionados a comportamentos sociais nessa atividade. A partir do que e observado, demonstra-se a importância de desenvolver pesquisas acerca do tema no contexto brasileiro.
Plateau 3: Visualising Soundscapes

Drawing together ideas from the previous three chapters I develop the concept of ‘the emergent dimension of play’ as a means of describing the nature of lived experience in the club. I explain how the ‘diverse acts’ seen in the club are characterised by spontaneity, exuberance / affect, imagination, performance and mischievousness, all of which could be considered to make up the ‘emergent dimension’ of play. I outline the implications of this concept, before explaining how the project’s methodological approach made this aspect of the lived experience visible. I return to the issue of visual and multimodal representation that runs throughout the book, considering issues of modal complexity, the benefits of using multiple modes to convey research and challenges inherent in doing so.
Evaluation of T-Way Testing of DNNs in Autonomous Driving Systems

A Deep Neural Network (DNN) model is used to perform intelligent, safety-critical tasks in Autonomous Driving Systems (ADS). In our prior work, we proposed a combinatorial testing approach to test DNN models used to predict a car's steering angle. We generate test images by applying a set of combinations of basic image transformations. In this paper, we report a preliminary study that compares the performance of synthetic images generated using a combinatorial approach to DeepTest, a state-of-the-art tool that aims at generating test inputs that maximize neuron coverage. We present an experimental evaluation by measuring and comparing the neuron coverage achieved using the two approaches. Two pre-trained DNN models from the Udacity driving challenge are used as the subject DNNs. The results suggest that the combinatorial approach performs better than the DeepTest approach in generating valid synthetic images and covering an additional number of neurons.
SECURITY ISSUES ON CLOUD COMPUTING

As we all know, Cloud computing is an emerging domain and the high-speed growth of the cloud has led to more cost-saving, elasticity, and scalability but it is also facing a large amount of privacy and security challenges. In this review paper, we will discuss cloud computing and its security issues.
[Application and Research Progress of Lineage Tracing in Differentiation Mechanism of Hematopoietic Stem Cells--Review].

Hematopoietic stem cells (HSCs) reside at the top of the hierarchy and have the ability to differentiate to variety of hematopoietic progenitor cells (HPCs) or mature hematopoietic cells in each system. At present, the procress of HSC and HPC differentiating to the complete hematopoietic system under physiological and stressed conditions is poorly understood. In vivo lineage tracing is a powerful technique that can mark the individual cells and identify the differentiation pathways of their daughter cells, it takes as a strong technical system to research HSC. Traditional lineage tracing studies mainly rely on imaging techniques with fluorescent dyes and nucleic acid analogs. Recently, newly cell tracing technologies have been invented, and the combination of clonal tracing and DNAsequencing technologies have provided a new perspective on cell state, cell fate, and lineage commitment at the single cell level. In this review, these new tracing methods were introduce and discuss, and their advantages over traditional methods in the study of hematopoiesis were summarized briefly.
Collaborative Approach to Translating Online Learning Content: Research Data Management Librarian Academy ( RDMLA ) and National Taiwan University ( NTU ) Library Translation and Co‐Creation Partnership

Abstract The Research Data Management Librarian Academy (RDMLA) is a global professional development online program for librarians and other professionals working in research‐intensive environments. To reach a broader learner community, the RDMLA team established a Chinese translation partnership with the National Taiwan University (NTU) Library in early 2020. Through collaborative problem solving, positive participation, inclusive coordination, and leveraging of teams' strengths, the project has succeeded in its mission, with the translated course due to launch in October 2021. Featuring team workflow illustrations and contributions, this poster covers collaborative translation processes and lessons learned, hoping to inspire similar international partnership projects.
QLEN: Quantum-Like Evidential Networks for Predicting the Decision in Prisoner’s Dilemma

For predicting the decision in prisoner’s dilemma game, researchers have developed lots of models. However, the existing models only consider the networks based on quantum probability amplitude and the accuracy can still be improved. Thus, in this paper, quantum-like evidential network (QLEN) is proposed, which is the evidential extension of the original quantum-like Bayesian network. A QLEN consists of a directed acyclic graph associated with quantum mass function. In addition, a full joint quantum mass function can be derived from QLEN which can be applied in decision making and inference. Moreover, based on QLEN, this paper presents a decision model for predicting the players’ decision in prisoner’s dilemma. The results show that, compared with the existing models, the proposed model is more efficient and accurate to make predictions in prisoner’s dilemma.
FSS:A Fast Switch System Based on AWGR for Optical Datacenter Network

A flexible and fast switch system based on AWGR to enable optical datacenter networks is proposed and numerically investigated. Results validate that the packet loss is less than 18.84%, latency is less than 11.7 <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mu \mathrm{s}$</tex> .
Диакритики в графической системе языка: нужно ли проставлять точки в ё?

The paper offers a sketch of a typological classification of diacritics, according to their role in the graphic system and their position in writing. The diacritics of the Russian writing are under consideration. The research focuses on the letter ё, highlighting traditions and practices of its use. The survey reveals current trends in the use of ё, based on attitudes of young people to it, and factors that influence the choice of ё when writing in different styles (formal/non-formal) and techniques: handwritten or printed (on the computer/other device). Ideological potential of the letter ё is noted, too.
Use of semantic technologies to inform progress toward zero-carbon economy: Extended Abstract

To investigate the effect of possible changes to decarbonise theeconomy, a detailed picture of the current production system is needed. Material/energy flow analysis (MEFA) allows for building such a model. There are, however, prohibitive barriers to the integration and use of the diverse datasets necessary for a system-wide yet technically-detailed MEFA study. Here we present a demonstration of the “Physical Resources Observatory” (PRObs) system, which exploits Semantic Web technologies to integrate and reason on top of this diverse production system data. We demonstrate how this system supports domain experts to load datasets, map them to the ontology, and query the extended data to meet several modelling use cases.
Teachers’ Instructional Interaction in an Inclusive Classroom: Interaction Between General Teacher and Special Assistant Teacher

The purpose of this study was to determine the categories of instructional interaction, the basic patterns of instructional interactions, and the functions of the basic model of instructional interaction that occurs between the English teacher (ET) and the special assistant teacher (SAT) to help the slow learner student (SLS), in terms of instructional interaction that occurs between two teachers in an English lesson. The researchers used single-case study method research. Data were collected through observation, as well as through semi-structured interviews with the two teachers. Findings from this study indicate that the category of instructional interaction that occurs between the two consists of academic and non-academic interactions. The instructional interaction basic patterns that are formed between ET and SAT in academic interaction are initiate-response-follow-up (IRF) and initiate-response (IR). The function of the basic pattern of academic interactions is to inform delegation of academic tasks from ET to SAT and to help SLS perform academic assignments. The instructional interaction basic pattern of non-academic interaction is initiate-response (IR). The function of the basic pattern of non-academic interactions is to enhance the provision of non-academic assistance from SAT to SLS, such as motivating, and focusing on learning. If instructional interactions between ET and SAT have not been carried out optimally, then the collaboration has not been well planned.
Blogging Our Way Through the Semester

Adapting an assignment for a hybrid class, students learned to consider business feasibility elements through blogging about an industry of their choice and then presenting a recorded “Ted Talk.” Lessons learned include that students are lacking in digital design skills and the ability to present in a story-telling format. Adding coursework in the future to increase these skills will prepare students for future careers that may include digital marketing activities.
SQ3R Method for Teaching Reading Narrative Text of the Tenth Grades at MA IslamiyahTanggulangin

This study aims to determine the effect of learning to read students using SQ3R method with student who don’t use the SQ3R method. The problem in this research is the difficulty of students in identifying a problem in a narrative reading text to determine the character, character, and setting in a story. In this study using a true experimental design research design with two classes in the control class and experimental class and two different treartment namely using treatment and not using treatment. In the control class in order to determine the effect on the two classes of researcher. On the result of the calculation of the classes in the control and experimental class there is a significant effect of students reading learning after being taught using the SQ3R method. Thus Ha: there is no significant effect of students reading learning after being taught using the SQ3R method. Ho: there is a significant effect of students reading learning after being taught using SQ3R method. In this explanation, it is evident that there is an influence of learning to read using the SQ3R method.
Referring Image Segmentation via Language-Driven Attention

This paper aims to tackle the problem of referring image segmentation, which is targeted at reasoning the region of interest referred by a query natural language sentence. One key issue to address the referring image segmentation is how to establish the cross-modal representation for encoding the two modalities, namely, the query sentence and the input image. Most existing methods are designed to concatenate the features from each modality or to gradually encode the cross-modal representation concerning each word&#x2019;s effect. In contrast, our approach leverages the correlation between the two modalities for constructing the cross-modal representation. To make the resulting cross-modal representation more discriminative for the segmentation task, we propose a novel mechanism of language-driven attention to encode the cross-modal representation for reflecting the attention between every single visual element and the entire query sentence. The proposed mechanism, named as Language-Driven Attention (LDA), first decouples the cross-modal correlation to channel-attention and spatial-attention and then integrates the two attentions for obtaining the cross-modal representation. The channel attention and the spatial attention respectively reveal how sensitive each channel or each pixel of a particular feature map is with respect to the query sentence. With a proper fusion of the two kinds of feature attention, the proposed LDA model can effectively guide the generation of the final cross-modal representation. The resulting representation is further strengthened for capturing the multi-receptive-field and multi-level-semantic for the intended segmentation. We assess our referring image segmentation model on four public benchmark datasets, and the experimental results show that our model achieves state-of-the-art performance
Point-rating system of knowledge assessment in geographical education

The article is devoted to the description and analysis of pedagogical experience of professional competence formation in training and assessment of students in the point-rating system. The interdisciplinary nature of geographical education implies the need to develop special ways of thinking among students and to attract knowledge and skills from different subject areas. In such a situation, it is necessary to maximize the arrangement of the training process from the initial stage of learning to the stage of summative assessment. The work contains proposals to supplement the evaluation tools of expertise, knowledge and skills with innovative methods to better understand the success of students educational activities. A system of measures used by the teacher during the semester for formative and summative assessments to evaluate the level of competence development in students is described. Emphasis is placed on the possibility of using distance learning technologies in the point-rating system. A conclusion is made on the effectiveness of the score-rating assessment of the competence development level in geographical education and predictive capabilities of this method of control, particularly in Master's and postgraduate studies. The concept of the score-rating system proposed in the article was tested by the author while teaching a number of geographical subjects at Ural State Pedagogical University. This methodology has proven to be an effective method of increasing the organization and motivation of students.
Fusion Incremental Kalman Estimator for Singular Systems under Poor Observation Condition

When the measurement equation of the system is not verified or calibrated under certain environmental conditions, using the measurement equation will often produce unknown system error, which will lead to large filtering error. The introduction of the incremental equation can effectively solve the state estimation problem of this kind of system under poor observation condition. In this paper, a descriptor incremental Kalman estimation algorithm is proposed for the linear discrete singular systems under poor observation condition. The problem of state estimation for singular systems with unknown observation error is solved, which cannot be solved by classical Kalman filter. Furthermore, under the linear minimum variance optimal fusion criterion, an optimal weighted fusion descriptor incremental Kalman estimator is proposed. Compared with the existing methods, the algorithm proposed in this paper has the advantages of simple form, low computational burden and easy application in engineering. A simulation example proves its effectiveness and feasibility.
A Framework for Estimation of Generative Models Through an Adversarial Process for Production of Animated Gaming Characters

Unsupervised training is used in generative models, in which the network is trained using only the input data and no suggested output. The model is then used to create output samples that are identical to the input values. GANs, or Generative Adversarial Networks, is a subcategory of generative models. GANs are a framework in which two opposing neural networks collaborate to produce outputs based on their learning. Discriminator and Generator are the two main subnetworks used by GANs. The Generator learns from the data and then produces a sample of the data it has learned from. The Discriminator is a binary classification model that uses a sigmoid function to give a value between 0 and 1 based on its decision on the input data, which is the Generator's output data, and the training data, and determines if the sample belongs to the actual data distribution or is a fake generated by the Generator. Both the Generator and the Discriminator compete to improve, with the Discriminator improving at classifying fake images and the Generator improving at producing fake images. When both networks are smart enough to form a good GAN, the Discriminator's accuracy should eventually approach 50%.
PKM Dialogue Practice Read the dialogue aloud with your teacher. Alex is at the bank in the USA, opening a new account. Bank Clerk Good morning, sir. How can I help you? Alex Good morning. I’d like to open a savings account, please. Bank Clerk All right, s

ABSTRACT&#x0D; Introduction: factors that cause students run into problems in learning English, among others lack of motivation, limited learning facilities, the absence of a container for them to practice vocabulary they have got, limited learning resources and shame to speak English. With the class room language makes it easy for students to remember the vocabulary which they have memorized. The aim of the study:To know About English and vocabulary used for classroom language in Junior High School Students at the Al Manar Orphanage, Ujung gurap. Materials and Methods: Extension activities about Using Classroom Language At Junior High School Students at the Al Manar Ujung Gurap Orphanage With the Lecture Method, Discussion and Question and Answer. Research result: Activities using Classroom Language get a positive response of students due to the class becomes even more active. Conclusion: As many as 87.5% of students have the ability in doing learning by using the classroom language.
Algorithms for Sparse Support Vector Machines

Many problems in classification involve huge numbers of irrelevant features. Variable selection reveals the crucial features, reduces the dimensionality of feature space, and improves model interpretation. In the support vector machine literature, variable selection is achieved by l1 penalties. These convex relaxations seriously bias parameter estimates toward 0 and tend to admit too many irrelevant features. The current article presents an alternative that replaces penalties by sparse-set constraints. Penalties still appear, but serve a different purpose. The proximal distance principle takes a loss function L(β) and adds the penalty ρ2dist(β,Sk)2 capturing the squared Euclidean distance of the parameter vector β to the sparsity set Sk where at most k components of β are nonzero. If βρ represents the minimum of the objective fρ(β)=L(β)+ρ2dist(β,Sk)2, then βρ tends to the constrained minimum of L(β) over Sk as ρ tends to ∞. We derive two closely related algorithms to carry out this strategy. Our simulated and real examples vividly demonstrate how the algorithms achieve better sparsity without loss of classification power. Supplementary materials for this article are available online.
Methodical approach to professional training of students of higher educational institutions

One of the important problems of training competitive specialists in creative professions is the theoretical substantiation and practical implementation of the idea of integrating science and technology, education and production, searching on this basis for innovative approaches to creative education. Taking this into account, the problem of integrating knowledge in higher education acquires significance and has a number of advantages. The university is faced with the task of providing students with a holistic, scientific, flexible system of knowledge, which is modified depending on the profile and purpose of each type of educational institution. One of the most effective ways to achieve this goal is to integrate the content, forms and methods of teaching into the educational process.