Reviewerly/exHarmony huggingface dataset:
Analisis Perbandingan Fitur Search Engine

&#x0D; &#x0D; &#x0D; Search engines are used in the web as a tool for information retrieval. Web Server is a large warehouse of heterogeneous and unstructured data so that to filter out relevant information from people, a search engine is needed. Search engines usually consist of page repositories, indexing modules, query modules and ranking modules. Search engines do not work alone, besides that there is a web browser that supports the work of this search engine to be more optimal. A browser is software that is run on a user's computer (user) that displays web documents or information taken from a web server [1]. A browser is the type of intermediary the user uses most often. This paper aims to analyze three search engines namely Google, Yahoo, and Bing based on existing features. These features include web search, image search, video search, news search, route search, book search, change search settings, display number of views, shopping, language translator. Google stands as the best search engine among all search engines, which works using the Page Rank algorithm. Page Rank is a numerical value that determines the importance of a web page by calculating the number of backlinks.&#x0D; &#x0D; &#x0D;
A note on depth-b normal elements

In this paper we study elements $\beta \in \mathbb{F}_{q^n}$ having normal $\alpha$-depth $b$; that is, elements for which $\beta, \beta - \alpha, \ldots, \beta-(b-1)\alpha$ are simultaneously normal elements of $\mathbb{F}_{q^n}$ over $\mathbb{F}_{q}$. In [1], the authors present the definition of normal $1$-depth but mistakenly present results for normal $\alpha$-depth for some fixed normal element $\alpha \in \mathbb{F}_{q^n}$. We explain this discrepancy and generalize the given definition of normal $(1-)$depth from [1] as well as answer some open questions presented in [1].
Weighted variational regularization image dehazing algorithm based on non-local prior

Abstract In hazy weather conditions, the quality of images taken outdoors will be degraded, so researching image dehazing has great practical significance. Therefore, an image dehazing algorithm based on non-local prior weighted variational regularization is proposed. Since the performance of the image dehazing algorithm depends largely on the accuracy of the estimated transmission, a classical non-local prior algorithm is first adopted to make a rough initial estimate of the transmission. Then a weighted variational regularization model is proposed to further optimize the initial transmission and solve the model by the alternating direction multiplier method. Finally, a haze-free image can be recovered directly from the atmospheric scattering model by using the optimized transmission. The experimental results verify that the proposed algorithm has higher image dehazing performance than several commonly used algorithms.
Pelatihan penulisan cerita anak berbasis nilai-nilai profetik bagi guru PAUD se-Kabupaten Gunungkidul

The training of children's stories based on prophetic values is an effort to support the diligent movement of writing and reading (Ratulisa). PAUD Desert in Gunungkidul Regency does not have the skills in writing children's stories. This program aims to empower PAUD teachers throughout Gunungkidul Regency to be skilled at making children's stories. The writing results are used as a short story collection book that can be used as teaching material. Implementation methods include training and practice including: understanding children's stories and prophetic values, (2) practice of story ideas, (3) practice of creating characters, (4) practice of creating settings, (5) determining conflict, (6) determining plot, (7) ) determine the language style of the story, (8) practice writing (9) independent work. The output of this activity is a children's story collection book and the realization of a writing culture. The implementation of PPM for PAUD teachers throughout Gunungkidul takes place from 5 April-10 September 2019. The PPM program has been running smoothly to produce a collection of children's stories. PPM programs need to be developed more broadly in various regions and sustainably. The program has the potential to increase interest in reading and writing so as to create a conducive learning atmosphere.
Preventing and Rectifying Cloud Quality of Service Violation Through Adaptive Resource Scaling and Replication&#x0D;

One major challenge in delivering and accessing cloud applications is the management of Quality of Services (QoS).It is mandatory for cloud service providers to ensure their performance and fulfil QoS, as defined in the Service Level Agreement (SLA).In this paper, we propose a Scaling and Fault Tolerance (SFT) algorithm to deploy preventive or remedial measures based on 16 decision rules for QoS violation detection and prediction.We simulate the SFT algorithm in a cloud simulator with four scenarios to measure its effectiveness in handling events such as faulty virtual machines (VMs), or over and under-provisioning of resources.Our experimental results show that the proposed SFT algorithm performs effectively (close to a 90%100% effective rate) in providing preventive or remedial measures and reducing the number of VMs when they are not needed.
Research and design of three-dimensional brain augmented reality system based on medical image features

With the rapid development of information technology and the application of artificial intelligence technology in medical field, the latest computer technology has become a means to improve the level of medical diagnosis. Various medical imaging diagnostic devices, such as CT and MRI, can provide two-dimensional images of human body information. At present, doctors urgently need to accurately determine the spatial position, size, geometric shape of the lesion and the spatial relationship between the lesion and surrounding tissues. Therefore, it is very important to use computer technology to reconstruct human organs and display the lesion area in three-dimensional. At present, the results of automatic recognition and labeling of brain images are displayed in two-dimensional form, so it is necessary to use three-dimensional visualization technology to reconstruct them. In addition, some additional information can be superimposed on brain images for integrated display by combining virtual and real information. Augmented reality is the best technology to achieve the above requirements. This paper studies the process of feature extraction and three-dimensional reconstruction of brain image diseases. Combining with augmented reality business function, using DICOM file and Unity tool, a program of three-dimensional reconstruction and visualization of brain image features is designed to help doctors grasp the spatial information of brain quickly and intuitively.
PENGARUH MODEL PEMBELAJARAN ARIAS MENGGUNAKAN PhET TERHADAP PEMAHAMAN KONSEP DAN MINAT BELAJAR

This research was conducted to determine the effect of ARIAS Learning Model Using PhETInteractive Media Simulations on the Understanding of Learning Concepts and Interests of Grade X Students of SMA Negeri 8 Palembang.This research uses quasi-experimental method with post-test only control group design.The population of this study was all students of class X consisting of 6 classes.The sampling technique uses cluster random sampling technique, and takes 2 classes as the experimental class and the control class.Retrieval of data using the instrument test understanding concepts and questionnaires of interest.The acquisition of t-test results is tcount = 3.957> ttable = 1.664 with α = 0.05; which means that there is a significant influence on the ARIAS Learning Model using PhET Media Interactive Simulations on Student Concept Understanding.And t-test results obtained tcount = 4.842> ttable = 1.664 with α = 0.05; which means that there is a significant influence on the ARIAS Learning Model using PhET Interactive Media Simulations on Student Learning Interests.The conclusion is that there is a significant influence on the ARIAS learning model using interactive media simulations of PhET on understanding concepts and learning interests compared to conventional learning.
The Cybersecurity Landscape in Healthcare

A new survey reveals that healthcare data breaches cost the industry billions, and is only expected to get worse.
Analysis of Reading Comprehension Skills Reviewed from the Literacy Level of Reading Students in Higher Education

Aim to research this for knowing the level of reading comprehension skills in terms of student literacy levels.The population of 300 students.Next, 171 samples of the maha students selected use a stratified random sampling technique.Instrument research is a questionnaire scale Likert and reading skills tests understanding.Data obtained analyzed with variance analysis ( Analysis of Variance / ANOVA).The results showed that the calculated F value obtained was equal to 5,179, while Sig. on the degrees of freedom (DK) 1 and alpha (α) 0.05 are 0.024, then according to the hypothesis testing criteria through analysis of variance (ANOVA), Sig.smaller than 0.05, which means that there are differences in the level of reading comprehension skills of students when viewed from the literacy level.Students who have high reading literacy, the level of reading skills are also high.
Developing a customized web mining system with PHP language: A case of Kaohsiung Land administration website data

With the growth of WWW, the unstructured data of web is full of useable information. But these available data are not easy to collect, access, and handle of large scale. Each company, it crawls the available data of site-specific Official or e-Commerce websites and storage huge number of data to progress the analysis of big data. But, here is a difficult question that needs to construct a data mining platform on Web server for companies. In this paper, we use PHP Language to develop a customized web mining system, taking a case of Kaohsiung Land Administration Website Data, defining a novel framework of web mining system, which can reduce cost of constructed platform and enhance efficient of Web crawler.
METODE PEMBELAJARAN BAHASA INGGRIS ANAK USIA DINI

This study aims to determine the knowledge of parents about early childhood English learning methods. The approach in this study uses qualitative using interview methods. the results of the study showed that of the 40 parents interviewed, 38 parents could mention the method used in learning English in early childhood while 2 parents could not mention an appropriate method for learning English in early childhood. methods that fit the characteristics and development of early childhood are conversation, playing, telling stories, singing, using pictures and playing roles.Keywords: early childhood English learning, learning methods, characteristics of early childhood
Setting Up a Cloud Server

As with most cloud providers, setting up a cloud server on Linode is extremely simple. This chapter shows you the basic process to get something up and running, with screenshots.
윤대녕 소설에 나타난 신화적 시공간 연구: - ‘틈’과 ‘길’을 통한 통과제의적 양상과 의미를 중심으로

Dae-nyeong Yun is considered to be a writer representing the 1990s literature, while presenting a new aspect of the 90s. Such an evaluation shows that Dae-nyong Yun has moved away from his ideological inclinations in the 1980s and shows stories about the inner workings of his personal side through ontological questions.One of the main pillars of the Dae-nyeong Yun’s novels is the mythical imagination. Based on this, this paper tries to find traces of mythological imagination based on the characters’ actions in the short and mid stories and focused on remarkable stories of time image and space image. Also, this paper check on the characters who follow the traces of the mythical imagination and process the rite of passage of the characters through M. Eliiade’s and Joseph Campbell’s suggestion.Time images and space images in Dae-nyeong Yun’s novels are a means for the main characters have questions or answers about ontological questions. In particular, the time images are approaching the essence of the self, using a gap in everyday life, by suggesting that the same events are repeated several times or instantaneous erasure of time. In addition, space images shows that the scene is reborn through a rite of passage throught actions on the passing road, not the place where the main characters, ‘the blue road of Silla’ and ‘the revival place of the sweetfish’ for example. Based on the above contents, this paper focused on the image of crack and road of in time images and space images of Dae-nyeong Yun’s novels.Dae-nyeong Yun’s novels are negatively evaluated, either on absence of the realism, or by using mythological elements to escape reality. Even though the characters in the novels linger in the distance and stay in space, they can not only leave it to the reality, but also to show that it is a positive sign that they return to the realities of life. In addition, it can be understood that the characters in his novels extend to the surrounding characters without limiting the character of the characters, which can be interpreted as a way to show and reflect on the underlying lives of more people through novels.There is not enough only in terms of mythological aspects in many of the works of Dae-nyeong Yun’s. But priorly the negative reviews of Dae-nyeong Yun’s novels, the characters of the novels suggest that the characters in the novel are choosing to confront the reality, not escape the reality of escaping the realities of reality.
Modules

A module packages a host of functionalities into a single file, often under a single name. Being as it is a multi-paradigm language, these modules come under different flavors, but two rough categories: solo routines and classes/roles/grammars. As you have seen previously, Perl 6 packs most functionality into classes, but not all of them are, and of course, it’s up to you to decide which one is the best for your problem.
The “Jump and Stay” Method to Discover Proper Verb Centered Constructions in Corpus Lattices

The research presented here is based on the theoretical model of corpus lattices.We implemented this as an effective data structure, and developed an algorithm based on this structure to discover essential verbal expressions from corpus data.The idea behind the algorithm is the "jump and stay" principle, which tells us that our target expressions will be found at such places in the lattice where the value of a suitably defined function (whose domain is the vertex set of the corpus lattice) significantly increases (jumps) and then remains the same (stays).We evaluated our method on Hungarian data.Evaluation shows that about 75% of the obtained expressions are correct, actual errors are rare.Thus, this paper is 1. a proof of concept concerning the corpus lattice model, opening the way to investigate this structure further through our implementation; and 2. a proof of concept of the "jump and stay" idea and the algorithm itself, opening the way to apply it further, e.g. for other languages.
Vectorized Discrete Gaussian Sampling with SIMD Support

Discrete Gaussian sampling is a fundamental building block of lattice-based cryptography. Sampling from a Gaussian distribution ð·â„¤,ðœŽ,ð‘ over the integers â„¤ is an important sub-problem of discrete Gaussian sampling, where parameter Ïƒ &gt; 0 and center c âˆˆ â„. In this paper, we show that two common sampling algorithms for discrete Gaussian distribution over the integers can be implemented more eï¬ƒciently by using vectorization with SIMD (Single Instruction Multiple Data) support. Speciï¬cally, we use the VCL (C++ vector class library) by Agner Fog, which oï¬€ers optimized vector operations for integers and ï¬‚oating-point numbers with the support of SIMD. The VCL is also a simple tool for constant-time implementations, which helps prevent the information leakage caused by the timing attacks on sampling operations.
Student Perceptions of Replacing Textbooks With a Mobile Application in the Classroom

To examine student perception of mobile and web-based apps compared to textbooks in occupational therapy education.
La incidencia de las emociones sobre los procesos de aprendizaje en niños, niñas y jóvenes en contextos de vulnerabilidad social

From Neuroscience perspective, emotions involve physiological, behavioral and cognitive changes. The nervous system gets involved in such responses. Child abuse, bullying or addictions in children and teenagers have a negative impact over their neuroendocrine and immune systems. Implications of this physiological vulnerability can cause changes on cognitive functions and have a negative impact over scholar development.
식품안전관리망 강화를 위한 블록체인 기술 도입의 적절성 평가

The appropriateness of introducing blockchain technology into food safety management systems was evaluated by conducting a survey of experts on the effectiveness and constraint evaluation indicators, and a portfolio analysis was conducted to set the priorities of blockchain application. The food safety management activities considered in this study were issuing documents on food import/export, food hygiene rating scheme, civil complaint management in the food sector, food- related certification, risk information management, and food traceability systems. The sectors that can be expected to be effective in the introduction of blockchain technology were food- related certification, food hygiene rating scheme, risk information management, and issuing documents on food import/export. In the case of food traceability systems and civil complaint management, the introduction of blockchain technology was not recommended due to ineffectiveness. From the evaluation of the constraints (e.g., technical limits, cost, legal amendment, personal information disclosure, timeliness, and ease of connection) to be overcome when introducing blockchain into food safety management, it was found that there are more than average constraints in all six areas. In particular, the food traceability system was evaluated to have the most constraints. Issuing documents on food import/export is very effective with the introduction of blockchain technology, but due to high cost and legal restrictions, it is necessary to improve the institutional system in order to introduce blockchain. Among the evaluation sectors, food- related certification, food hygiene rating scheme, and risk information management on foods were suitable for preferentially adopting blockchain technology since these areas might experience greatly improved reliability and transparency through the introduction of blockchain, with relatively low constraints.
The Implementation of Jigsaw Technique on Narrative Text

&lt;p&gt;This study is conducted to find out and to describe to what extent the use of Jigsaw Technique improves the students’ reading comprehension, and to describe the classroom situation when Jigsaw Technique is implemented in reading class. The population of this study is the students of grade VIII in a state junior high school in Boyolali in the academic year 2017/2018 consists of 21 students. The data were collected by observation, interview, and test. The research findings showed that the teacher dominated the teaching-learning process, while the students were not active to give responses but passive to ask questions. The brief explanation of this study can be presented as follows. The first students reading ability could be improved through the use of Jigsaw technique, before the research was done, the average score of the students’ reading ability was only 59.6, but after the research one for cycle 1, it improved to 65. In cycle 2, it increased up to 71.5. Next, there were also improvements of class situation in teaching learning process and it helps to improve students’ reading ability and more engaged in learning process.&lt;/p&gt;
Speech Perception and The Role of Semantic Richness in Processing

The richness of meaning associated with specific words has been found to influence word recognition. Such findings, however, have come largely from studies based on visual word recognition, and related studies focusing on the acoustic signal and speech perception are less common. The present work recognizes that any effects observed may vary across modalities, and explores semantic richness effects as they may pertain to the perception and processing of spoken language. Goh et al. (2016) describe an auditory lexical decision experiment where concreteness, valence, arousal, semantic neighborhood density, and semantic diversity are found to affect spoken word recognition. The stimuli used in their study were limited to a set of fewer than 500 words, most of which were concrete nouns. In our study, we expand the scope of the analysis to include 9,086 words taken from the Massive Auditory Lexical Decision database (MALD; Tucker et al., 2019), each with corresponding values for each of the semantic variables of interest. In complement to the results described by Goh and colleagues, generalized additive mixed modelling indicates significant effects of concreteness, valence, arousal, and semantic neighborhood density on response latency. No effect was observed for semantic diversity. These results suggest that the processing of acoustic signals is influenced by top down semantic effects, even in decontextualized environments. While the specifics of these effects differ by semantic variable, it appears that increased semantic richness facilitates spoken word recognition.
Satellite Telemetry Anomaly Morphology Extraction Based on Normal Mode Gap Mining

It is difficult for conventional data mining methods to find out non-frequent and long-sequence satellite telemetry anomaly morphology, and the mining results are not compact and lack of time continuity. In this paper, an anomaly morphology extraction algorithm NPGM-AMEA for telemetry data based on normal pattern gap mining is proposed. Firstly, the satellite telemetry parameters are discretized by KT-Means algorithm, and the original telemetry parameters are converted into feature strings. Secondly, the feature pattern mining is carried out to obtain the feature pattern of telemetry normal sequence, that is, the frequent closure of feature string;Then, the gap between adjacent normal feature modes is located to obtain the location of the abnormal pattern; Finally, the abnormal feature string between the normal mode gaps are extracted and the abnormal curve shape of telemetry state is obtained by matching the abnormal feature string with the time series data. The correctness and reliability of the method are verified by the simulation experiment of abnormal shape mining of the telemetry parameters of a certain type of satellite.
Combining Clinical Data and Domain Knowledge for Analyzing Mental Disorder Concept Relatedness and Usage

Concept relatedness played a significant role in biomedical domain as it facilitates a number of tasks including information extraction, natural language processing, concept clustering and classification. In this research, we leveraged concept embedding to measure concept relatedness and compared concept relatedness based on embedding to the Gold standard concept classification. We also used real-world data from mental health domain to measure concept usage. The results revealed that compatibility accuracy measure F score was 0.21 and about 20% of SNOMED Mental Disorder concepts are utilized for patient cohort selection task. This study contributed a method for exploring concept relatedness and usage, and different approaches to medical concept classification, providing insights for medical ontology developers and domain experts.