Reviewerly/exHarmony huggingface dataset:
DEVELOPING AND LEARNING HOW TO OPTIMIZE EARLY CHILDHOOD ACTIVITY THROUGH PLAYING

God's Son is very valuable deposit. Created as a small human child, but not a miniature of adult. The child has unique characteristics and different from adults. Kids are in a phase where he is being kept growing and growing, both physical and psychological potential. In general, children have properties that active, dynamic, enthusiastic and curious about everything he saw, heard and felt. Kids seemed to have a surplus of energy to continue to explore. Early childhood (0 to 8 years old) is a time of fundamental important where the process of growth and development occurs very rapidly in the span development of human life. Developments acquired at an early age are affecting the development at a later stage and increase labor productivity in adulthood. A kid has potential to be better in the future, but that potential can only thrive when given a stimulus, guidance, support and treatment in accordance with the level of growth and development. Playing is a child's world, because the play is a very fun activity for them. Playing is a need that already exists (inhern) in children. Playing contribute naturally to learn and grow, and there is no single program that can replace observations, activities and direct knowledge of children at play. One way children get the information for children is through play. When children have a fun gaming experience with materials, objects or other children, along with the support of a parent or adult, the child will develop optimally. Parents or adult emotion should be wise in supporting the process of learning and help children achieve optimal development.
A latent variable model for two-dimensional canonical correlation analysis and the variational inference

Describing the dimension reduction (DR) techniques by means of probabilistic models has recently been given special attention. Probabilistic models, in addition to a better interpretability of the DR methods, provide a framework for further extensions of such algorithms. One of the new approaches to the probabilistic DR methods is to preserving the internal structure of data. It is meant that it is not necessary that the data first be converted from the matrix or tensor format to the vector format in the process of dimensionality reduction. In this paper, a latent variable model for matrix-variate data for canonical correlation analysis (CCA) is proposed. Since in general there is not any analytical maximum likelihood solution for this model, we present two approaches for learning the parameters. The proposed methods are evaluated using the synthetic data in terms of convergence and quality of mappings. Also, real data set is employed for assessing the proposed methods with several probabilistic and none-probabilistic CCA based approaches. The results confirm the superiority of the proposed methods with respect to the competing algorithms. Moreover, this model can be considered as a framework for further extensions.
Automatic Construction of General Non-Recurrent Neural Network Using Genetic Programming

An Artificial Neural Network (ANNs) is a model that has been studied for many years in the hope of achieving human like performance. It was used in many applications like (pattern recognition, signal processing, vision, speech recognition, and decisions making aids and robotics).There are many types of ANNs, most of these types are suffering from some problems such as Convergence, Design and some of these ANNs cannot solve the non-linear problems.Since Genetic Programming (GP) is a machine learning technique used in the automatic induction of computer programs, therefore we used it as automatic system for designing and implementing ANNs trying to overcome the previous problems.In this paper we proposed an approach to build ANNs based on evolutionary computation, which uses the GP to evolve both the architecture and weights of General non-recurrent NN simultaneously. New GP modification operations were proposed which are (structure-preserving crossover, structure-preserving mutation, and structure-preserving permutation), these modification operations have clear effects in improving the results of the proposed system.The proposed system has been used in solving five simple problems which are (AND, OR, NOT, Exclusive-OR, and Half-Adder) problems. In addition, we compare the results of the proposed system with Koza work and with three major types of supervised ANNs, which are (Perceptron, Back-Propagation, and Adaline).
Projecting "better than randomly": How to reduce the dimensionality of very large datasets in a way that outperforms random projections

For very large datasets, random projections (RP) have become the tool of choice for dimensionality reduction. This is due to the computational complexity of principal component analysis. However, the recent development of randomized principal component analysis (RPCA) has opened up the possibility of obtaining approximate principal components on very large datasets. In this paper, we compare the performance of RPCA and RP in dimensionality reduction for supervised learning. In Experiment 1, study a malware classification task on a dataset with over 10 million samples, almost 100,000 features, and over 25 billion non-zero values, with the goal of reducing the dimensionality to a compressed representation of 5,000 features. In order to apply RPCA to this dataset, we develop a new algorithm called large sample RPCA (LS-RPCA), which extends the RPCA algorithm to work on datasets with arbitrarily many samples. We find that classification performance is much higher when using LS-RPCA for dimensionality reduction than when using random projections. In particular, across a range of target dimensionalities, we find that using LS-RPCA reduces classification error by between 37% and 54%. Experiment 2 generalizes the phenomenon to multiple datasets, feature representations, and classifiers. These findings have implications for a large number of research projects in which random projections were used as a preprocessing step for dimensionality reduction. As long as accuracy is at a premium and the target dimensionality is sufficiently less than the numeric rank of the dataset, randomized PCA may be a superior choice. Moreover, if the dataset has a large number of samples, then LS-RPCA will provide a method for obtaining the approximate principal components.
Designing Interactive Gui With Matlab

In this paper we introduce a tutorial on the use of the Guide facility of MATLAB.Guide is a development platform composed of several interrelated tools within MATLAB that allows the user to build complex graphical user interfaces that can be used as teaching tools or as automated programs.Several examples related to engineering disciplines are presented.
Pengaruh Penerapan Pembelajaran Berorientasi Aktivitas Siswa Dan Motivasi Belajar Terhadap Prestasi Belajar Siswa Kelas IX SMP Negeri 3 Kabupaten Pamekasan

This research related to Implementation of instruction based students’ activities and Students’ learning Motivation toward students’ learning achievementt of Ninth Grade Students State Junior High School 3 Pamekasan regency . The students’ learning achievementt is influenced by Implementation of instruction based students’ activities. Additionally it is influenced by Students’ learning Motivation. Good and regularly Implementation of instruction based students’ activities brings a positive effect on the students’ learning achievement and a high learning motivation in teaching will increase the students achievement. The purpose of this research is (1) to describe Implementation of instruction based students’ activities toward students’ learning achievement. (2) to describe the significant influence of the Students’ learning Motivation toward students’ learning achievement . (3) to describe the significant influence of Implementation of instruction based students’ activities and Students’ learning Motivation simultaniously toward students’ learning achievement. The design of this research is descriptive quantitative. The subject of the research is Ninth Grade Students of State Junior High School 3 Pamekasan. The data collecting technique is by giving some questionnaires. Data analyzing technique used patial and multi-regression computerized SPSS 17.00 program for windows. The Result and the discussion as follows: a) There is a significant influence on the Implementation of instruction based students’ activities (X1) toward students’ learning achievement is about 0,312. b) There is a significant influence on the Students’ learning Motivation (X2) toward students’ learning achievement is about 0,062 by the significanct level 0,000, on t-account, that means smaller than 0,05. It can be concluded that X1 and X2 are very significant. c) There is a significant influence on the Implementation of instruction based students’ activities and Students’ learning Motivation simultaneously toward students’ learning achievement is about 17,617 by the significanct level 0,000, on F-account, that means smaller than 0,05. It can be concluded that X1 and X2 are very significant toward Y.
USING SHORT STORY TO IMPROVE STUDENTS’ VOCABULARY ACHIEVEMENT OF THE GRADE IX STUDENTS OF SMP NEGERI 6 PANGSID SIDRAP REGENCY

The objective of the research was (1) to find out whether or not the use of short story to improve the students’ vocabulary achievement of Grade IX Students of SMP Negeri 6 Pangsid, (2) to find out which aspect of vocabulary was dominantly affected by short story at SMP Negeri 6 Pangsid. This research employed the method of the research was quasi-experimental research method. Two classes were selected using cluster random sampling technique, 25 students each. One by experimental group, and the other by control group. The experimental group was taught by short story method and the control group was taught by non-short story or conventional method. The data were collected use vocabulary test administered to experimental group and control group before and after treatment. The treatment was conducted for eight meetings for experimental group and control group. The data was analyzed using SPSS 20.0 version. The result of the t-test value in posttest (20.294) was higher than t-table (2.010) while the t-test value of control group (4.164). This means that H1 was accepted. The research concluded that (1) teaching vocabulary by using short story increased the students’ vocabulary at the ninth year of SMP Negeri 6 Pangsid and (2) the aspect that most affected was word meaning, it was proven by the interval score was higher among the others aspects (85.20).
Influencing User Choices in Interactive Narratives Using Indexter’s Pairwise Event Salience Hypothesis

Indexter is a plan-based model of narrative that incorporates cognitive scientific theories about the salience — or prominence in memory — of narrative events. A pair of Indexter events can share up to five indices with one another: protagonist, time, space, causality, and intentionality. The pairwise event salience hypothesis states that a past event is more salient if it shares one or more of these indices with the most recently narrated event. In a previous study we used this model to predict users’ choices in an interactive story based on the indices of prior events. We now show that we can use the same method to influence them to make certain choices. In this study, participants read an interactive story with two possible endings. We influenced them to choose a particular ending by manipulating the salience of story events. We showed that users significantly favored the targeted ending.
Smart Web Services (SmartWS) -- The Future of Services on the Web

The past few years have been marked by an increased use of sensor technologies, abundant availability of mobile devices, and growing popularity of wearables, which enable the direct integration of their data as part of rich client applications. Despite the potential and added value that such aggregate applications bring, the implementations are usually custom solutions for particular use cases and do not support easy integration of further devices. To this end, the vision of the Web of Things (WoT) is to leverage Web standards in order to interconnect all types of devices and real-world objects, and thus to make them a part of the World Wide Web (WWW) and provide overall interoperability. In this context we introduce Smart Web Services (SmartWS) that not only provide remote access to resources and functionalities, by relying on standard communication protocols, but also encapsulate `intelligence'. Smartness features can include, for instance, context-based adaptation, cognition, inference and rules that implement autonomous decision logic in order to realize services that automatically perform tasks on behalf of the users, without requiring their explicit involvement. In this paper, we present the key characteristics of SmartWS, and introduce a reference implementation framework. Furthermore, we describe a specific use case for implementing SmartWS in the medical domain and specify a maturity model for determining the quality and usability of SmartWS.
MVPN and MSDP SA Interoperation

This document specifies the procedures for interoperation between MVPNSource Active routes and customer MSDP Source Active routes, which isuseful for MVPN provider networks offering services to customers withan existing MSDP infrastructure. Without the procedures described inthis document, VPN-specific MSDP sessions are required among the PEsthat are customer MSDP peers.
Energy Savings When Migrating Workloads to the Cloud

In the cloud environment, data centers are efficiently manipulated by cloud service providers (CSPs) in terms of energy consumption. Consequently, migrating workloads to clouds can result in lower energy consumption. This paper demonstrates that the Lift-and-Shift migration with optimal selections of cloud instances can provide significant energy savings, and explains how much and where the energy savings are obtained from. Additionally, the analysis on the variation of energy consumption is given when Auto-Scaling is deployed showing that further energy savings are expected even without refactoring applications. All the conclusions and analyses are based on the real data collected by Cloudamize Inc. from May 2016 to August 2016 over 40,000 machines across approximately 300 data centers.
Long-term Viability of Protocol Extension Mechanisms

The ability to change protocols depends on exercising the extensionand version negotiation mechanisms that support change. Protocols thatdon't use these mechanisms can find that deploying changes can bedifficult and costly.
Future Vector Enhanced LSTM Language Model for LVCSR

Language models (LM) play an important role in large vocabulary continuous speech recognition (LVCSR). However, traditional language models only predict next single word with given history, while the consecutive predictions on a sequence of words are usually demanded and useful in LVCSR. The mismatch between the single word prediction modeling in trained and the long term sequence prediction in read demands may lead to the performance degradation. In this paper, a novel enhanced long short-term memory (LSTM) LM using the future vector is proposed. In addition to the given history, the rest of the sequence will be also embedded by future vectors. This future vector can be incorporated with the LSTM LM, so it has the ability to model much longer term sequence level information. Experiments show that, the proposed new LSTM LM gets a better result on BLEU scores for long term sequence prediction. For the speech recognition rescoring, although the proposed LSTM LM obtains very slight gains, the new model seems obtain the great complementary with the conventional LSTM LM. Rescoring using both the new and conventional LSTM LMs can achieve a very large improvement on the word error rate.
THE USE OF BATAVIA LANGUAGE IN EAST JAKARTA (STUDY OF SOCIODIALECTOLOGY)

Abstract: This research is to describe the use of Betawi language used by native speakers or natives or at least have lived for ten years in East Jakarta with sociodialectological studies which include descriptions of the use of Betawi in phonology and lexical fields as well as descriptions of similarities and differences in Betawi in East Jakarta. The research method used is a comparative descriptive method. Data collection is done using the method of field mixing, which is a method of collecting data directly or verbally. In addition, the method used is the synergy method. Research techniques used, namely note taking and fishing techniques. The conclusion of this research is the existence of several similarities and differences, both in the fields of phonology, morphology, lexicon, or syntax. From the 806 words we obtained from speakers in each region, researchers found 235 differences in the same lexicon and 571 lexicon in the four study areas. The conclusion of this research is at the level of phonology, morphology, lexicon, and syntax there is considered no difference. Keywords: Language, Betawi, East Jakarta.
MENINGKATKAN KEMAMPUAN MENYELESAIKAN OPERASI HITUNG PERKALIAN MELALUI PENGGUNAAN MEDIA TALI PAS

This study aims to describe students' activeness of the class when it is applied to the media and the improvement of learning outcomes of the students of grade V SDN Paciran I Lamongan 2016/2017 academic year in completing multiplication counting operation through the use of laces. This research belongs to classroom action research. Data obtained in the form of formative test results, observation sheet of teaching and learning activities. The learning outcomes of multiply counting operations by applying the wrist strap medium from cycle 1 to cycle 2 experience, a very satisfactory improvement. In cycle 1, there is an increase of students who fulfill KKM that is 50%, while in cycle 2 reach 100%.
Oriented Convex Containers of Polygons -- II

We define an 'oriented convex region' as a convex region with a direction of symmetry. An earlier article had touched upon isosceles triangles, rectangles and ellipses. Here, we examine some more possible oriented containers - semicircles, segments of circles and sectors - and raise some questions.
Hubungan Ganguan Akibat Kekurangan Yodium (GAKY) dengan Prestasi Belajar di SDN Tanggalrejo Kecamatan Mojoagung Kabupaten Jombang

The Correlation Of Iodine Deficiency Disorder (IDD) With Learning Achievement At Public Ementary School ( Sdn ) Tanggalrejo Village , Mojoagung Sud District , In Jombang District. One nutritional problem In indonesia is IDD. IDD is known to be able to effect abnormality such as mumps, cretin, intelligence disorder, mental disorder and physical development disorder that affect the quality of HR (Human Resources). Impaired intelegence of child, make the child will have difficulty to achieve learning. The research aimed to understand the correlation of IDD with learning achievement at ( SDN ) Tanggalrejo Village, Mojoagung Sub district in Jombang District. This research was an analytic correlation with cross sectional approach. The population as much as 54 respondent was the students of grade 3 at Public Elementary school ( SDN ) Tanggalrejo Village Mojoagung sub district in Jombang District , and total of samples was 54 respondents with the technique of sampling used total sampling. The independent variable was Iodine deficiency Disorders(IDD) and the dependent variable was learning achievement with the instrument in the form of inspection and palpation of thyroid gland and documentation of the value with Spearman rank test. The results showed that the most (70.4%) IDD was 0 degrees and the most (33.3%) learning achievement was less , it was obtained r value = 0.351, ρ = 0.009 and ɑ = 0.05, because ρ &lt;ɑ then Ho was refused it meant there was correlation of IDD with grade 3 student ‘s achievement at Public Elementary School (SDN ) Tanggalrejo Village , Mojoagung Sub district in Jombang District.Based on the description above, so that the increase of iodized salt consumption is needed by school-age children to prevent the emergence of new problems, and as a correction for people with IDD. And necessary counceling about the important iodized salt to community. Keywords: IDD, Learning Achievement
Optimised DWT using cooperative particle swarm optimiser for hybrid domain based medical and natural image denoising

The quest for productive image denoising systems still is a valid challenge, at the intersection of practical investigation and measurements. In spite of the sophistication of the recently proposed systems, most calculations have not yet achieved an attractive level of applicability. In this research, an optimal wavelet filter coefficient design-based methodology is proposed for image denoising. The method utilises new wavelet filter whose coefficients are derived by discrete wavelet (Haar) transform using CPSO optimisation and bilateral filter. The optimal wavelet coefficient based denoising methods minimise the noise, while bilateral filter further decreases the noise and increases the PSNR without any loss of relevant image information. Overall, the proposed approach consists of two stages namely, (i) design of optimal wavelet filter, (ii) image denoising using a bilateral filter. At first, wavelet optimal coefficients are selected using cooperative particle swarm optimiser (CPSO). After that, the hybrid domain based algorithm (wavelet with bilateral filter) is applied to the noisy image which is helpful to obtain the denoised image. A comparative study of the performance of different existing approaches and the proposed denoised approach is made in terms of PSNR, SDME, SSIM and GP. When compared, the proposed algorithm gives better PSNR compared to the existing methods.