Reviewerly/exHarmony huggingface dataset:
An Analysis of Outlier Detection through clustering method

This research paper deals with an outlier which is known as an unusual behavior of any substance present in the spot.This is a detection process that can be employed for both anomaly detection and abnormal observation.This can be obtained through other members who belong to that data set.The deviation present in the outlier process can be attained by measuring certain terms like range, size, activity, etc.By detecting outlier one can easily reject the negativity present in the field.For instance, in healthcare, the health condition of a person can be determined through his latest health report or his regular activity.When found the person being inactive there may be a chance for that person to be sick.Many approaches have been used in this research paper for detecting outliers.The approaches used in this research are 1) Centroid based approach based on K-Means and Hierarchical Clustering algorithm and 2) through Clustering based approach.This approach may help in detecting outlier by grouping all similar elements in the same group.For grouping, the elements clustering method paves a way for it.This research paper will be based on the above mentioned 2 approaches.
Improving the Speaking Skill by Vlog As Learning Media for Teaching Long Functional Text For Eighth Grade Students at SMPN 17 Medan

This research was aimed to develop Video Blog as media of speaking in teaching long functional text for eighth grade students at SMPN 17 Medan. This research applied Research and Development (R&amp;D) model proposed by Gall, Gall and Borg (2003) through six procedures: gathering data and information, conducting need analysis, designing, expert validating, revising, and producing final product. The subjects of this research were 30 students of eighth grade of SMPN 17 Medan. The instruments of collecting data were the teacher’s lesson plan, teacher’s interview and students’ questionnaires result. The data were analyzed by using descriptive analysis. The product has been validated by two experts. The assessment from the first expert was 4,5 or 91,3% while the assessment from the second expert was 4,6 or 93%. Based on the experts’ judgment result, the research showed that: The Video Blogs were eligible and valid as learning media in teaching and learning speaking long functional text for eighth grade students at SMPN 17 Medan. Furthermore, the video blogs give many benefits for students, such as to improve their speaking, make them enjoy and easier to speak long functional text. It means that the vlog media development was appropriate for the eighth grade students of SMPN 17 Medan.
A Simple and Effective Usage of Word Clusters for CBOW Model

We propose a simple and effective method for incorporating word clusters into the Continuous Bag-of-Words (CBOW) model. Specifically, we propose replacing infrequent input and output words in CBOW with their clusters. The resulting cluster-incorporated CBOW model produces embeddings of frequent words and a small amount of cluster embeddings, which will be fine-tuned in downstream tasks. We empirically demonstrate that our replacing method works well on several downstream tasks. Through our analysis, we also show that our method is potentially useful for other similar models that produce word embeddings.
Dynamic Computation of Threshold Value for Classifying Jobs in Cloud Computing for Efficient Resource Utilization

Cloud computing is an instant use of resources and it is a trending technology in the field of computer science. Here, many jobs will be arriving continuously with different job size, at that point of time, allocating of resources for suitable virtual machines without allowing virtual machine to starving is a hindrance job. So, to avoid this hindrance, an algorithm Dynamic Computation of Threshold Value is proposed (DCTV) and based on the threshold value the jobs are classified in the initial stage, so this classification leads to allocation of resources precisely and efficient resource utilization. The experimental result shows that by using dynamic computation of threshold value the allocation of resource time is reduced and classification accuracy is improved compared to manual computation of threshold value.
Why can information not be defined as being purely epistemic

The concept of information can be viewed from two perspectives, namely epistemic and ontological. In the epistemic view, information is associated with meaning, semantics, and knowledge, while in the ontological view, it is understood as structures and forms of objects. Information is most often perceived as epistemic information, yet a closer look at epistemic information reveals that this concept does not account for ontological information. This paper poses the following question: Should we select epistemic or ontological information as our primary concept of information, or should we acknowledge that both kinds of information are required for a full comprehension? The discussion here is supported by references to modern research in physics, computing, cosmology, and information sciences.
The Effec Of Contextual Teaching And Learning Method In Writing English Paragraph At English Depeartment FKIP Nommensen Pematangsiantar

This study is aim to know the Effect of Contextual Teaching and Learning Method on the Students’ ability in Writing Paragraph at English Department of FKIP Nommensen Pematangsiantar. This research was an experimental study which conducted quantitative analysis. The population of this research was Group C and D students of English Department FKIP Nommensen Pematangsiantar Academic year 2018/2019. There were two classes. The samples of this research were taken from two classes. They were group C that consists of 45 students stated as the experimental class, and group D that consist of 25 students stated as the control class. After analyzing the data, the writer found that there was a significant effect of using Contextual Teaching and Learning Method to the students’ ability in writing paragraph. The Mean Score was 11,72 and the value of t-test was higher than t-table (t-test &gt; t-table), 5,208 &gt; 1,996. Ha (Alternative Hypothesis) was accepted and Ho (Null Hypothesis) was rejected. It can be concluded that by using contextual teaching and learning method, the students were encouraged to do writing paragraph in their daily life. The students have abilities to identify their weakness, accepted their mistakes and recognized their potential.
Frequency of co-occurrence of chinese characters as an indicator of lexicality (when selecting the vocabulary of chinese military discourse)

Teaching a foreign language in a non-linguistic college or university should be professionally oriented, which brings up the question of selecting the relevant vocabulary of a professional discourse under study. Modern text corpora are too general in subject matter and the time span. Therefore, a specially compiled collection of texts can serve the purpose of selecting the vocabulary. In the case of the Chinese language, the task is complicated by the lack of word segmentation in such texts. Taking into account the fact that most words in Chinese are written in two characters, it is assumed that one of the methods applicable in this situation is a comprehensive frequency analysis of text sequences of two characters – character bigrams. The analysis of frequent bigrams has showed that 70% of the most frequent lexical units are representative of the discourse, including 11% of out-of-vocabulary ones. The remaining part of bigrams pertain to syntactic constructions, including structurally incomplete ones, and fragments of longer lexical units. Thus, the high frequency of character co-occurrence can with a rather high probability (p &gt; 0.7) be considered as an indicator of lexicality in identifying representative vocabulary in an unsegmented the matic collection of texts in Chinese.
Blur More To Deblur Better: Multi-Blur2Deblur For Efficient Video Deblurring

One of the key components for video deblurring is how to exploit neighboring frames. Recent state-of-the-art methods either used aligned adjacent frames to the center frame or propagated the information on past frames to the current frame recurrently. Here we propose multi-blur-to-deblur (MB2D), a novel concept to exploit neighboring frames for efficient video deblurring. Firstly, inspired by unsharp masking, we argue that using more blurred images with long exposures as additional inputs significantly improves performance. Secondly, we propose multi-blurring recurrent neural network (MBRNN) that can synthesize more blurred images from neighboring frames, yielding substantially improved performance with existing video deblurring methods. Lastly, we propose multi-scale deblurring with connecting recurrent feature map from MBRNN (MSDR) to achieve state-of-the-art performance on the popular GoPro and Su datasets in fast and memory efficient ways.
Information and physics

This is an overview article that contains the discussion of the connection between information and physics at the elementary level. We present a derivation of Lindauer’s bound for heat emission during irreversible logical operation. In this computation the Szilard’s version of Maxwell’s demon paradox is used as a model to design thermodynamic implementation of a single bit of computer memory. Lindauer’s principle also motivates the discussion on the practical and emergent nature of the information. Apart from physics, the principle has implications in philosophy.
Data Balancing Method for Training Segmentation Neural Networks

Data imbalance is a common problem in machine learning and image processing. The lack of training data for the rarest classes can lead to worse learning ability and negatively affect the quality of segmentation. In this paper, we focus on the problem of data balancing for the task of image segmentation. We review major trends in handling unbalanced data and propose a new method for data balancing, based on Distance Transform. This method is designed for using in segmentation convolutional neural networks (CNNs), but it is universal and can be used with any patch-based segmentation machine learning model. The evaluation of the proposed data balancing method is performed on two datasets. The first is medical dataset LiTS, containing CT images of liver with tumor abnormalities. The second one is a geological dataset, containing of photographs of polished sections of different ores. The proposed algorithm enhances the data balance between classes and improves the overall performance of CNN model.
METHODOLOGICAL AND TECHNICAL DESIGN OF INNOVATIVE CLASSROOM

The prepared report on the MoPED project contains information on methodological and technical design of the innovative class. The modern educational challenges and trends are analyzed, the changes that take place in modern education are highlighted, in particular the peculiarities of the organization of modern education in comparison with the traditional one. Different approaches to determining the list of skills of the XXI century, which should be formed in the process of modern learning. The concepts and features of STEM / STEAM / STREAM approaches in comparison with traditional teaching are described and their advantages are defined, psychological and pedagogical features of modern pupils which need to be considered at designing of use of innovative methods and means of training are considered. The modern principles of assessment are covered, the peculiarities of formative assessment are given, the ways of organization of joint educational activity of students, problem-based learning and project activity are offered. Relevant innovative pedagogical technologies of teaching and their features are determined. The concept of blended learning and models of its implementation, as well as the method of research and cognitive learning (Inquiry Based Learning - IBL) are considered. The main characteristics of the ICR class are presented and recommendations for different organization of rotation stations in the educational process are given. The report presents the results of a study conducted by the authors on the use of digital tools in the innovation classroom.
Method for Improving an Image Segment in a Video Stream Using Median Filtering and Blind Deconvolution Based on Evolutionary Algorithms

Video surveillance systems, dash cameras and security systems have become an inescapable part of the most institutions ground environment. Their main purpose is to prevent incidents and to analyze the situation in case of extemporaneous events. Though as often as not it is necessary to increase an image segment many times over to investigate some incidents. Sometimes it is dozens of times. However, the obtained material is mostly of poor quality. This is connected either with noise or resolution characteristics, including focal distance. The paper considers an approach for improving image segments, which were obtained after multiple zooming. The main idea of the proposed solution is to use methods of blind deconvolution. In this case, the selection of restoration parameters is carried out using evolutionary algorithms with automatic evaluation of the result. That seems like the most important detail here is pre-processing besides noise minimization within the image, because when the image is repeatedly enlarged the effect of the noise component also increases. To avoid this thing, we suggest using ordinal statistics and average convolution for a series of images. The proposed solution was implemented as a software product, and its operation was tested on a number of video segments made under different shooting conditions. The results are presented at the end of this article.
Comparative Evaluation of Metals and Heavy Metals in Some Yemeni Crude and Fuel Oil

Due to high importance of the crude oil to the modern society as a source of energy and as raw material for a wide chemical and petro chemical industries. In this study we made assessment of metals and heavy metals in some Yemeni crude, and fuel oils namely Mareb crude oil blend, Masila crude oil blend plus two samples from Sounah and Hijah oil fields in Masila basin. Fifteen metals and heavy metals were determined in above samples, but the most indicated were ( Na, K, Mg, ) and ( V, Co, Ni ) using ICP technique and atomic absorption spectroscopy . The order of concentration of metals in Yemeni crude oils were as shown in figures: Na &lt; K &lt; Co &lt; Mg &lt; V &lt; Ni &lt; Ca&lt; Fe &lt; Cd &lt; Al&lt; Zn &lt; Cr &lt; Cu &lt; Pb &lt; Mn. In Fuel oil: Na &lt; Co &lt; V &lt; Mg &lt; K &lt; Ni &lt; Ca &lt; Fe &lt; Al &lt; Cd &lt; Zn &lt; Cr&lt; Pb &lt; Mn &lt; Cu. Comparing concentrations of metals in studied sample, in general were less than in crude oil and fuel oil in many countries. That mean Yemeni crude and fuel oil are the best in quality. The order of concentration of metals in Yemeni crude oils were as shown in figures: Na &lt; K &lt; Co &lt; Mg &lt; V &lt; Ni &lt; Ca&lt; Fe &lt; Cd &lt; Al&lt; Zn &lt; Cr &lt; Cu &lt; Pb &lt; Mn. In Fuel oil: Na &lt; Co &lt; V &lt; Mg &lt; K &lt; Ni &lt; Ca &lt; Fe &lt; Al &lt; Cd &lt; Zn &lt; Cr&lt; Pb &lt; Mn &lt; Cu. Comparing concentrations of metals in studied sample, in general were less than in crude oil and fuel oil in many countries. That mean Yemeni crude and fuel oil are the best in quality.
USE OF WEB 2.0 TOOLS BY POLISH HEALTH PORTALS

The Internet, as a global, universal communication network, has become an important channel of information distribution. Currently, it has a very social character, thanks to the dissemination of Web 2.0 sites, which allow users to create and publish their own multimedia content. Web 2.0 technologies make it easier for users to communicate, create, collaborate and share information. They are widely available and are characterized by low costs of use. The article presents the results of research on the most popular Polish health websites. It was examined whether health services meet the requirements of Web 2.0 sites. The analysis is focused on the technological and social aspects. The COVID-19 pandemic lockdown in March and April 2020 in Poland was observed as having an influence on users and views of heath websites. The obtained results confirm the use of elements (both technological and social) by health services selected for research. However the usage of Web 2.0 technologies among websites varies.
Multi-Stream Refining Network for Person Re-Identification

Viewpoint change, pose variation and background clutter have adverse impacts on similarity evaluation for person re-identification.Because of its distinction and reliability, person saliency has been applied to model person appearance characteristics.However, such valuable information is not fully exploited to compute similarities of person images with existing deep methods.To this end, we present a novel multi-stream refining based deep multi-task learning scheme that aggregates multi-stage salient embedding features in the network to boost the retrieval performance.Specifically, the backbone network is divided into four stages and a channel significance self-learning sub-module is introduced to strengthen the importance of saliency channels adaptively.Meanwhile, an enhancement sub-module is employed to extract the common information and different information from the channels.Finally, a multi-stream multi-task learning framework combining four-stage branches is adopted to learn discriminative features.Compared with the state-of-the-art approaches, our model achieves competitive performance on three publicly available datasets, i.e., Market-1501, MSMT17, and CUHK03.The experimental results demonstrate the superiority of our method, which achieves 95.67%/88.51%,87.53%/65.54%,and 89.32%/78.99% on Rank-1/mAP, respectively.
Interdependence of Bitcoin and Other Crypto Money Indicators: CD Vine Copula Approach

In recent years, there has been a growing interest on the combination of copulas with mixture model. The combination of vine copulas incorporated into a finite mixture model is also helpful to capture secret structures in a data. This paper aims to examine the relationship between bitcoin and other crypto money indicators with the CD Vine Copula Approach method. In the study, we use closing prices of Bitcoin, Bitcoin Cash, Ethereum, Litecoin, and IOT. The results show that there is a strong dependence between bitcoin and prominent financial indicators.
The experience of distance learning for students of Altai State University in the conditions of COVID-19

Abstract In the global information and educational era with the increasing importance of information technology, distance learning allows acquiring high-quality professional education by means of the access to educational and additional materials, a fast way of transferring information in the process of interaction between a student and teachers. Due to COVID-19 coronavirus infection pandemic, the management of Altai State University decided to transfer the pedagogical process to distance learning for the safety of students and teachers, minimizing the need for their physical presence in classrooms. However, for a classical university, the forced transition to full distance learning requires a careful analysis associated with both the assessment of the effectiveness of training and the formation of students’ motivation.
Statistical analysis of the relationship between type II radio enhancement and solar energetic particle event

In this paper, we investigated 82 type-II radio burst events detected by some ground stations Learmonth, YNAO, and BIRS and spacecraft Wind/WAVES, STEREO/WAVES from January 2007 to December 2015. And we identified 39 events associated with radio enhancement and 43 events without enhancement. We found that: 1) The CME velocity, mass, kinetic energy and flare class with respect to type II radio enhancement events were generally higher than that of no enhancement events, and these properties in the solar energetic particle (SEP) events were significantly higher than that no SEP event, regardless of whether radio enhancement or not. 2) As shown in the characteristic time analysis, the initial release time of SEPs is generally earlier than the start time of radio enhancement, so we can the radio enhancement is only as a signature of the shock enhancement rather than the direct generator of SEP events. 3) Whether radio enhancement or not, the onset height of type IIs associated with SEP event is slightly lower than that of event without SEP. For the absence height, the SEP events are significantly higher than the no-SEP events, and that the absence height of enhancement events are also distinctly higher than that non-enhancement events, which reveals that the enhanced CME shock characterized by enhanced radio burst can keep propagating to more higher or further space. 4) When one fast and wide CME fully sweeps over another slow and narrow preceding CME, CME interaction can more easily generate radio enhancement, but no distinctive difference between SEP events and non-SEP events. So the results of this paper reveal that radio enhancement can be regarded as a manifestation of CME shock becoming strong during interacting with other CME, and the enhanced shock can accelerate the particle to generate large SEP events more easily. However, the type II radio enhancement is not the direct producer or causer that generate large SEP event.
Revenue Analysis of Edge Computing Devices in Blockchain-Based IoT Networks

Internet of things (IoT) is a new technology connecting devices to the Internet from a wide variety of sectors. IoT devices can sense and collect massive data. Due to the limited computing ability of IoT devices, the edge computing is introduced to provide computing resources for IoT devices. However, how to ensure the security of interaction process between IoT devices and edge computing devices is a key issue. In this paper, the blockchain technology is introduced to realize the decentralized resource interaction between IoT devices and edge computing devices. A revenue function of edge computing device, which includes the revenue from providing the computing resources for IoT devices, and the revenue from participating in the consensus process of blockchain networks, is proposed. The numerical simulation results show that when the unit revenue of consensus computing is greater than that of IoT computing, the revenue of the blockchain-based resource allocation method is greater than that of the method without blockchain.
Talking Stick Learning Model, How Significant Has the Impact on the PGSD Students’ Speaking Skills?

This study aims to identify differences in the PGSD students’ speaking skills with and without talking stick learning model. This study uses a quantitative approach with a quasi-experimental design. The population was all students in the 4th semester with a total of 324 students. It involved 78 sample students selected using purposive sampling. Data were collected using speaking tests, observations, and interviews. The collected data were then analyzed using the Mann Whitney test. The result showed the Sig value of 0.000 which is lower than 0.05 and the average improvement in speaking skills of the experimental group is higher than the control groups. In conclusion, there are significant differences between students who received the talking stick learning model and those who did not