Reviewerly/exHarmony huggingface dataset:
IMPROVING STUDENTS’ READING COMPREHENSION THROUGH RECIPROCAL TEACHING STRATEGY ON REPORT TEXT

The objectives of this research is to know how to use of reciprocal methods to teaching reading comprehension of the senior high school in second grade. The purpose of the research is to help students’ to cope the difficulties in reading report text, because there are still many students who find it difficult to read English and the lack of reading comprehension of students in class XI Animation of SMK TI Garuda Nusantara Cimahi with the aim of (1) how to implement the Reciprocal Learning method in increasing students' reading comprehension (2) whether there is an increase in student scores after using the Reciprocal Learning method. The author uses the reciprocal method to increase the ability of students to read comprehension. This research is quantitative by using experimental research methods. After conducting the research obtained the data pre-test (80) and post-test (95). Based on these data, it can be concluded that the use of reciprocal methods in the report text material can improve reading comprehension in students of class XI Animation 2 Vocational School of TI Garuda Nusantara Cimahi.
Kirja masina ekstaatiline ümberkonstrueerimine / The Ecstatic Reconstruction of the Writing System Machine

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A Platform for Measuring the Response Time of Smartphones

Abstract Smartphones are playing an increasingly important role in helping people share information and communicate with each other, as evidenced by an increasing number of applications (or apps), including news, search engine, mailbox, and social networking apps. The more heavily people rely on their phones, the more they begin to take the term “user experience” into consideration when buying a smartphone. Obviously, the key to providing a good user experience is to minimize the response time of each graphical user interface (GUI) operation, such as a touch, slide, or flick. Thus, it is crucial for smartphone manufacturers and mobile app developers to measure the response times to enhance the performance of the device or application. In this article, the authors present the SMArtphone Response Time measuring platform (SMART), a novel and low-cost platform for measuring the response time of a smartphone. SMART consists of a normal 30-fps (frame per second) webcam and a mirror. The proposed platform first simultaneously records the changes on a smartphone screen and the GUI operation shown in the mirror. It then adopts image processing techniques to analyze the latency of the GUI operation. The authors’ validation results show that the measurement error of SMART is less than 1/30 s, which means that SMART is a practical solution for measuring the latency of GUI operations. In addition, they adopted SMART for the measurements and analysis of six different commercial smartphones to further demonstrate its applicability.
PERSEPSI GURU PENJAS SEKOLAH DASAR TERHADAP ANAK GEMUK DI KECAMATAN SEMARANG TENGAH

&lt;p&gt;&lt;em&gt;The purpose of this study was to find out how the perceptions of primary school teachers in Central Semarang District were. This type of research is qualitative with a phenomenological approach. Data was collected by in-depth interview and observation methods. Research subjects were 8 people consisting of 3 health teachers, 3 regular teachers, 1 vice principal and 1 principal. Data were analyzed by means of content analysis.&lt;br /&gt; The results showed that the perceptions of the primary school teachers in Central Semarang Subdistrict showed concern about the condition of obese children while doing material in sports lessons, but the teacher also felt very happy and excited about the fat child. The feeling of excitement and excitement is still quite large so that the feeling of worry is not too big. The teacher is still considering the child's obesity is not a problem if the fat child can still do sports / movement material well not inferior to other children. The teacher also does not have great hopes / desires / motivations so that the fat child is less fat and becomes normal again. Perceptions like this will make the teacher's action not too strict / not too strong in overcoming child obesity problems.&lt;br /&gt;&lt;/em&gt;&lt;/p&gt;
SYSTEM APPROACH TO EVALUATION OF E-TRAINING QUALITY

The article deals with evaluation of students' development within the traditional mode of training in universities and e-learning online.The research is relevant for practitioners as it is responsive and applicable to the needs of modern digital education.The paper gives detailed description of evaluation resources and characterizes effective e-learning on the example of e-training complex SmartEnglish online that is built on the bases of psychopedagogical laws of eco-humanistic self-development.Evaluation strategy has been developed as a result of the long term scientific investigation of learning process efficiency under natural condition of university training including e-learning online.A complex of quality control performed by experts and tutors is presented.Its validity and reliability are shown.Special attention is given to students' self-evaluation.Both theoretical and empirical approaches have been used for defining training efficiency.The research contains empirical results and observations as heavy emphasis is placed on the experimental data.For supporting evaluation process special computer programs have been designed.They provide professional tests and inventories for defining level of individual cognitive and personal development.The results are processed mathematically and accumulated in the database.They are developed and presented in the format of 1) histograms, 2) comparative tables, 3) profiles of personal development in the context of e-training aims.As expected, the positive correlation of metacapacities and metaqualities with sense-cognitive orientation of a personality is revealed.The links between the level of individual metacharacteristic development and comprehensiveness of sense-cognitive orientation are discovered.It opens the possibility of efficient purposeful https://doi.org/10
Model Based Co-clustering of Mixed Numerical and Binary Data

Co-clustering is a data mining technique used to extract the underlying block structureBouchareb, Aichetou between the rows and columns of a data matrix. Many approaches have been studied and have shown their capacity to extractBoullé, Marc such structures in continuous, binary or contingency tables. However, very little work has been done to perform co-clustering on mixed type data. In this article, weClérot, Fabrice extend the latent block models based co-clusteringRossi, Fabrice to the case of mixed data (continuous and binary variables). We then evaluate the effectiveness of the proposed approach on simulated data and we discuss its advantages and potential limits.
Influence of Continuous Professional Development on the Improvement of Ordinar-Level English Language Teachers’ Competencies

Existing research on small group learning with high-achieving students has been divided; although some researchers argue that this technique is detrimental to high-achievers, others endorse benefits for all learners.The current study aimed to assess whether academic achievement is associated with students' perspectives on small group learning.Forty-seven (47) children between the ages of 6-12 years participated in the study by answering questions pertaining to group learning.Students' academic achievement was assessed via their report card grades.A binomial logistic regression failed to find that academic achievement was predictive of the likelihood that students preferred working alone, however, a second binomial logistic regression discovered that higher achieving students were more likely to report that they learn better individually as opposed to in groups.This provides additional context for previous studies, by suggesting that perhaps it is not that high-achievers do not enjoy group work, but rather, they feel more confident in their individual abilities.
PELATIHAN KESIAPSIAGAAN BENCANA PADA SISWA SD MELALUI PERMAINAN EDUKATIF “AKSANA”

Bengkulu Province is an area located on three tectonic plates namely Indo-Australia, Eurasia, and Pacific which contain potential natural disasters such as earthquakes and tsunamis. Therefore, it is very important to prepare the community to be prepared for the disaster, including children. In every event of a disaster, there are many victims of children. Providing of knowledge and skills will minimize loss of life. Considering the importance of disaster preparedness, disaster preparedness training activities are carried out through educative games “AKSANA”. The word of AKSANA means Anak Sadar Bencana. This disaster preparedness training was attended by 30 students of SDN I Kota Bengkulu. School selection based on high level of disaster potential. SDN I is surrounded by beaches and is in the lowlands with a distance of less than 1 km from the beach. The service method is through AKSANA games consisting of disaster ladder snake, crosswords, and playbook about a disaster. In this activity, it was equipped with a simulation of self-rescue during an earthquake at the school accompanied by the PMI of Bengkulu Province. The effectiveness of disaster preparedness training in elementary school children was indicated by a significant increase in the pre-test and post-test scores from the average category (6.4) to high (8.9). With the increase in test scores, it shows that disaster preparedness training through AKSANA games can improve the knowledge and skills of students of SDN 1 Kota Bengkulu in dealing with natural disasters.
Effects of 5E learning Cycle Model on Achievement in Social Science of Std-8

Education is the most potent instrument of individual development, social transformation and means of national development.It helps to individual to acquire knowledge, skills and attitudes, which enable them to develop their faculties in full and thereby improve the quality of life for themselves, their communities and the nation as a whole.The objective of the study is to find the effect of 5 E learning cycle model on Achievement in Social Science in Std.-8 .The lesson transcript for teaching selected content based on 5E learning cycle model developed by Rodger Bybee of 'The Biological Science Curriculum Study is planned for study.The sample of the study has been selected in two stages.Purposive sampling technique was adopted for selecting the schools from Surat city, than two sections of eighth standard in both the schools lottery method was used to select the classes for the experiment.The section consisted of 60 students.Randomized pretest posttest match design was adopted as the research design for the study The mean, standard deviation, 't' test and ANOVA are the statistical technique used.It is concluded that it is significant difference on Achievement score of Experimental and control group and 5E learning cycle model is more effective in enhancing Achievement in Social Science when compared to Traditional Method.
The Earthquake Song to Improve Early Childhood’s English Vocabularies in Indonesia

The research was conducted with the aim to know the effect of music and movement on the vocabulary abilities of english words of early childhood in kindergarten of children 5-6 years old in Indonesia. This is an experimental research using pretest-posttest design. This research was conducted On January and early February 2019. The subjects of this study were group B, which amounted to 30 children 16 boys and 14 girls. The object of this research is the ability of english vocabulary in children. the data about the ability of english vocabulary of children through giving the performance assessment instruments. From the results of the research obtained, the influence between music and movement on the english vocabulary abilities of children with PV values = 5.311 with a total R-value of 68 or 0.683 r is higher than r-total using polled variance with a significance level of 5% or 0, 05. While the results of the t-test show that the value of t = -8.34 and t-table 0.683, in other words, the t-score is higher than the t-table or p-value&gt; alpha then H0 is rejected or Ha is accepted. There is an influence of motion and song on children's vocabulary abilities in kindergarten of children 5-6 years old. Through music and movement, children can learn vocabulary effectively and concretely. Children do every component of language, listening, speaking, reading, and writing also moving.
Implementation of A Static Images Protection Method in “Quantum World”

This study deals with the mechanism of protection of static (fixed) images, based on the permutation of image points (IP), inscribed in the edges of a regular hexagonal pyramid. In contrast to the classical methods of generating permutations, in which the elementary permutation operation is a permutation of two elements, in the proposed method the elementary operation is parametric, i.e. depends on the input parameters of the algorithm, and can affect the permutation of more than two IP. In the previous paper the rotation of hexagon was chosen as elementary permutation. In the present paper several possible modifications of the elementary permutation are considered, and on the basis of the analysis (criterion) of the number of realizable permutations of the initial sequence of IP (SIP) the most acceptable type of modification for the elementary permutation was chosen. The mechanism of protection of static (fixed) images using the permutation is proposed. The analysis of the persistence of this protection mechanism from attacks such as «brute force» is given, and an option that uses the redundancy of the graphical presentation is proposed. Applied analysis of given mechanism has demonstrated its ability to withstand modern cryptanalytic attacks in the application of quantum computing.
Soft Computing Techniques Based Image Classification using Support Vector Machine Performance

In this paper we compare different kernel had been developed for support vector machine based time series classification.Despite the better presentation of Support Vector Machine (SVM) on many concrete classification problems, the algorithm is not directly applicable to multi-dimensional routes having different measurements.Training support vector machines (SVM) with indefinite kernels has just fascinated consideration in the machine learning public.This is moderately due to the fact that many similarity functions that arise in practice are not symmetric positive semidefinite.In this paper, by spreading the Gaussian RBF kernel by Gaussian elastic metric kernel.Gaussian elastic metric kernel is extended version of Gaussian RBF.The extended version divided in two waystime wrap distance and its real penalty.Experimental results on 17 datasets, time series data sets show that, in terms of classification accuracy, SVM with Gaussian elastic metric kernel is much superior to other kernels, and the ultramodern similarity measure methods.In this paper we used the indefinite resemblance function or distance directly without any conversion, and, hence, it always treats both training and test examples consistently.Finally, it achieves the highest accuracy of Gaussian elastic metric kernel among all methods that train SVM with kernels i.e. positive semi-definite (PSD) and Non-PSD, with a statistically significant evidence while also retaining sparsity of the support vector set.
THE VALUE OF DIGITAL EVIDENCE IN CRIMINAL INVESTIGATIONS

Modern information systems, such as e-learning, e-voting, e-health, etc., are often used inappropriately for irregular data changes (data falsification). These facts force to review security measures and find a way to improve them. Proof of computer crime is accompanied by very complex processes that are based on the collection of digital evidence, forensic analysis and investigation. Forensic analysis of database systems is a very specific and complex task and therefore is the main source of inspiration for research. This article presents the fact that classical methods of collecting digital evidence are not suitable and effective. To improve efficiency, a combination of well-known, world-independent database technologies and their application in the field of forensic science are proposed. It also offers new directions for research in this area.
Research on Profile Vision Measurement Calibration

A calibration pattern with linear light method for profile vision measurement is proposed. A plan for calibration pattern is made which of the pattern pins can fold back to pattern plate in accordance with rows separately. The unfolding pattern pins are photographed with linear light crossing that vertically one row at a time. The mathematical expression of transforming physical plane into pixel plane is derived by physical coordinates and pixel coordinates. With the least-square method the calibration coefficient is made. The method is validated through the means that magnetic gauge block used as a higher precision measurement standard is close to the profile. The experiment indicates that it is avoided that the pattern pins from different rows interrupt the linear light, and the profile measurement error is better than 0.2 mm.
An Approach to Improve the Live Migration Using Asynchronized Cache and Prioritized IP Packets

The live migration of a virtual machine is a method of moving virtual machines across hosts within a virtualized data center. Two main parameters should be considered for evaluation of live migration; total duration, and downtime of migration. This paper focuses on optimization of live migration in Xen environment where memory pages are dirtied rapidly. An approach is proposed to manage dirty pages during migration in the cache and prioritize the packets at the network level. According to the evaluations, when the system is under heavy workload or it is running within a stress tool, the virtual machines are intensively writing. The proposed approach outperforms the default method in terms of number of transferred pages, total migration time, and downtime. Experimental results showed that by increasing workload, the proposed approach reduced the number of sent pages by 47.4%, total migration time by 10%, and the downtime by 27.7% in live migration.
The Exploration and Application of K-medoids in Text Clustering

Clustering algorithms is a statistical analysis method for classifying samples/indexes.The traditional text clustering algorithm is complicated and not convenient for data processing.Therefore, we proposed a new text clustering algorithm based on K-medoids.The new text clustering algorithm combines document category with semantics contribution.The new clustering algorithm can not only optimize the document frequency, but also take consideration of influence of the document category on the characteristic weight.The new text clustering algorithm was shown as follows: first, combine the proposed semantic contribution with fuzzy cluster, and vested the document (with no category information) category thereby; then we proposed the category information entropy and combined it with the semantic contribution in order to modify the traditional TF-IDF weight calculation method.We found the new text clustering algorithm was superior to the traditional weight calculation method after testing it in open platform of Chinese text categorization corpus data set.Therefore, we concluded that the new text clustering algorithm might have vast foreground of application.To solve the shortcomings of the traditional weight calculation method of feature items, text clustering algorithm based on K-medoids was proposed.The frequency and inverse document frequency were improved, and the influence of document category on feature weight was further studied.At the same time, because there may not be any standard classification datasets in practice, a new weight calculation method combining category and semantic contribution was proposed.First, the semantic contribution was proposed and then combined with fuzzy clustering.A text set with category information was obtained by rough clustering of text set without category information.Then, the category information entropy was proposed and combined with the semantic contribution to improve the traditional TF-IDF weight calculation method.Thus, a more effective weight calculation method was obtained.The Chinese text categorization corpus dataset in open platform of Chinese natural language processing of Fudan University was used for testing.The results showed that the new method for weight calculation of feature items was superior to the traditional weight calculation method.It is concluded that the improved text clustering algorithm can be used in a wider range of occasions.
A New Aesthetic QR Code Algorithm Based on Salient Region Detection and SPBVM

Many aesthetic QR code algorithms are proposed. In this paper, a new aesthetic QR code algorithm, based on salient region detection and Selectable Positive Basis Vector Matrix (SPBVM), is proposed. Firstly, the complexity of texture features are added to calculate the saliency values of the image, based on the existing salient region detection algorithms. According to the saliency map, the important area of the image is preserved for the subsequent beautification operation. Then, the appropriate basis vectors are selected by using the proposed SPBVM according to the acquired salient region, and the salient region is displayed completely by XOR operation which is performed by the original QR code and the selected basis vectors. Finally, the aesthetic QR code is obtained by combining the background image and original QR code. The results show that the proposed algorithm can produce more accurate salient area and have more pleasant visual effects.
The Function of Statement in Crowd Management and Crowd Control

Based on the Research of past incident, we have observed that different factors such as failure to recognize risks, crowd attitude, deficiency of the egress signage system, inconsistency among procedure, behavior & protocol; plan and environmental constraints etc. have affected crowd evacuation / release. Above all, the human component is the important factor in safety and disaster management, although it is bound to other components inextricably. This article discusses crowd attitude that may influence an emergency situation, and explain the method applied to the crowd prediction. Depending on hazard marking relative to crowd density, hazard plans for various phases are forwarded todispose the abeyant threats.Also practical crowd management calculated at various hazard phases are discussed; in the case of Kolkata metro fire: thick dark smoke filled compartment, passengers gasped for breath and other events.Finally, the schemes for crowd security management suggested that all stakeholders are amenable, to form risk consciousness and accomplish safety protocol consistent with hazard procedure professionally & scientifically.
Storage of Biometric Data in Database

Storage of multi-biometric information is required to encourage quick inquiry in expansive scale biometric frameworks.Past works tending to this issue in multibiometric databases concentrated on multi-case ordering, fundamentally iris information.Scarcely any works tended to the ordering in multi-modular databases, with fundamental competitor list combination arrangements restricted to joining face and unique mark information.Iris and unique finger impression are generally utilized in vast scale biometric frameworks where quick recovery is a critical issue.This work proposes joint multi-biometric recovery arrangement dependent on unique finger impression and iris information.This arrangement is assessed under eight distinctive hopeful rundown combination approaches with variable multifaceted nature on a database of 10,000 reference and test records of irises and fingerprints.Our proposed multi-biometric recovery of unique finger impression and iris information brought about a decrease of the miss rate (1-hit rate) at 0.1% entrance rate by 93% contrasted with unique finger impression ordering and 88% contrasted with ordering.