Reviewerly/exHarmony huggingface dataset:
Survey on iterative and incremental approaches in distributed computing environment

Iterative computation has become increasingly needed for a large and important class of applications such as machine learning and data mining. These iterative applications typically apply computations over large-scale datasets. So it is desirable to develop efficiently distributed frameworks to process data iteratively. On the other hand, data keeps growing over time as new entries are added and existing entries are deleted or modified. This incremental nature of data makes the previously computed results of iterative applications stale and inaccurate over time. It is hence necessary to periodically refresh the computation so that the new changes can be quickly reflected in the computed results. This paper presents the existing distributed systems that support iterative and incremental computations on large-scale datasets. It describes the main optimisations and features of these systems and identifies their limitations.
KALANDUE ANADARA GRANDIS SEA SHELLS AS ECO-FRIENDLY FLOOR FINISH MATERIALS

A high low energy in buildings is determined in the potential use of materials. Tile material is potentially made by architects as a sustainable building material. The use of tiles was marginalized by ceramic flooring products produced by large industries. The result of studies on the issue of global warming note that the embodied CO2 from the tile floor is almost seven times more than the embodies CO2 tiles. This result shows that tile products are environmentally sound and sustainable compared to tile floors. In another side, Kendari City is a Coastal City, and there are Kampung KB (Family Planning) that much mothers in this village busy every day with searching metti-metti/kalandue (Anadara grandis). During this time, shell kalandue fisherman catches only utilized meat/adductor muscle, while the shell is removed and uses as waste. In order for the tile to be competitive and interesting to be used as the floor of the house, it is necessary to study to create a tandem-based kalandue. This research is intended to create a tandem-based kalandue that used exploration method. The process of analysis is done qualitatively, so it gets the form of a tile. The shape of the tiles is transformed from the parameters to the resulting tandem-based kalandue shell. This study concluded that kalandue sea shells as eco-friendly floor finish material made, as follows: the working tools used were simple and sufficient. The working materials used are quite available and economical. The making process is done quickly and easily.
Image Semantic Segmentation Based on Depth Parallel Convolutional Networks

Fully convolutional network can effectively learn the task of centrally predicting pixels, such as semantic segmentation. However, FCN has the problems of spatial invariance and non-real time, which limits its performance and application. We propose an improved structure that preserves the basic shape of the FCN while extracting high-level features in the input section and introduces a separate residual learning module. On the other hand, we also introduce sub-networks that exist in parallel and reduce the size of the original FCN structure by proportional random discarding. Experiments show that the proposed method, which increases the residual network and parallel FCN and random discarding has better evaluation index than the traditional FCN method, and can further reduce the computational cost of the system with ensuring performance.
An Electro-Mechanical Input Device for the Manipulation of Virtual Human Motion

This paper describes an innovative methodology which automatically creates a 2D-axisymmetric finite element (FE) model of a quasi-axisymmetric component from its 3D CAD model.The process has been implemented as a script and uses the API to a commercial FE package.The calculation of a volume shape coefficients to be applied in the non-axisymmetric regions of the FE model, to account for the fact the region is not fully axisymmetric, is also described.In the paper, the methodology is demonstrated for a rotating blade of tapered profile analyzing and comparing both stresses and displacement.Excellent results are shown.
An improved algorithm to handle noise objects in the process of clustering

Cluster analysis is considered as an approach for unsupervised learning. It tends to recognise hidden grouping structure in a set of objects using a predefined set of rules. Objects occupying unusual characteristics add noise to the data space. As a result, complexities and misinterpretation in clustering structures will arise. This study aims at proposing a novel iterative approach to eradicate the effect of noise objects in the process of deriving clusters of data. Performance of the proposed approach is tested on partitioning, hierarchical and neural network based clustering algorithms using both simulated and standard datasets supplemented with noise. An improvement in the quality of clustering structure resulted from the proposed approach is witnessed, compared to that of conventional clustering algorithms.
MINIMIZING DISTORTION IN STEGANOG-RAPHY BASED ON IMAGE FEATURE

There are two defects in WOW.One is image feature is not considered when hiding information through minimal distortion path and it leads to high total distortion.Another is total distortion grows too rapidly with hidden capacity increasing and it leads to poor anti-detection when hidden capacity is large.To solve these two problems, a new algorithm named MDIS was proposed.MDIS is also based on the minimizing additive distortion framework of STC and has the same distortion function with WOW.The feature that there are a large number of pixels, having the same value with one of their eight neighbour pixels and the mechanism of secret sharing are used in MDIS, which can reduce the total distortion, improve the antidetection and increase the value of PNSR.Experimental results showed that MDIS has better invisibility, smaller distortion and stronger anti-detection than WOW.
Assessment of short-term breast cancer risk using a frequency domain correlation based imaging marker

Currently, mammography is the only population based breast cancer screening modality. In order to improve efficacy of mammography and increase cancer detection yield, it has been recently attracting extensive research interest to identify new mammographic imaging markers and/or develop novel machine learning models to more accurately assess or predict short-term breast cancer risk. Objective of this study is to explore and test a new quantitative image marker based on the analysis of frequency domain correlation based features between the bilateral asymmetry of image characteristics to predict risk of women having or developing mammography detectable cancer in a short-term. For this purpose, we assembled an image dataset involving 1,042 sets of “prior” negative mammograms. In the next subsequent “current” mammography screening, 402 cases were positive with cancer detected and verified, while 642 cases remained negative. A special computer-aided detection (CAD) scheme was applied to pre-process two bilateral mammograms of the left and right breasts, generate image maps in frequency domain, compute image features, and apply a multi-feature fusion based support vector machine based classifier to predict short-term breast cancer risk. By using a 10-fold crossvalidation method, this CAD based risk model yielded a performance of AUC = 0.72&plusmn;0.04 (area under a ROC curve) and an odds ratio of 5.92 with 95% confidence interval of [4.32, 8.11]. This study presented a new type of mammographic imaging marker or a machine learning prediction model and demonstrated its feasibility to help predict short-term risk of developing breast cancer using a large and diverse image dataset.
RANCANG BANGUN SISTEM E-SPORT CYBERCAFE FINDER MENGGUNAKAN METODE LBS (LOCATION BASED SERVICE) BERBASIS ANDROID

Abstract - The android mobile mapping application is very popular nowadays because it really helps people for daily activities, especially helping gamers especially to find the location of the nearest cybercafe that has qualified specifications to play eSport games, the rapid world of eSport gaming which has more international tournaments. more and more people are focusing on becoming an esport gaming athlete, every esport game requires high computer specifications in order to play it smoothly and without hindrance, this is where the role of cybercafe is, cybercafe provides high-specification computer facilities which are capable of accommodating various eSport games like Dota -2, CS:GO, PUBG, Fortnite, and others. And this application is a liaison between gamers and cybercafe locations located, this application uses the very relevant LBS method used in an application based on the mapping concept, this application is created using an android studio which is thought to be qualified to make an application that is user friendly and easy to use, besides this application also requires an internet connection because it is connected directly to google maps, navigation is very important in the operation of this application. KeyWords - cybercafe, maps, location based service, android mobile, android studio.
Влияние современных тенденций развития общества на формирование компетенций руководителя образовательной организации

The article presents the results of the analysis of education characteristics of preparation of experts in energy saving and energy efficiency in institutions of higher education, based on expert opinion (employers and experts in energy saving and energy efficiency).
PERANCANGAN APLIKASI UNTUK MENDETEKSI SABUK PENGAMAN MOBIL MENGGUNAKAN ALGORITMA BACKPROPAGATION NEURAL NETWORK (BPNN)

Abstract - To enforce traffic regulations on the highway, police officers face obstacles in monitoring the use of seat belts on cars because cars on the highway are always on the move and almost all cars use window film to avoid the heat of the sun entering the car. Based on the above problems, the authors build a software that can monitor or detect drivers wearing seat belts or not with Microsoft Visual C # 2010. To monitor the use of seat belts, digital cameras are used to conduct image acquisition to be processed by computers. . Furthermore, the image is studied by a system using the Back Propagation Neural Network (BPNN) Artificial Neural Network method as the image of the driver using a seat belt. To make a detection, the test image is input that is the same size as the training image. The test results obtained the level of accuracy for image acquisition with a distance of 1 meter with a similarity using a seat belt with a maximum value of 9% and a degree of similarity without a seat belt of less than 4%. Keywords - Image, Neural Network, Backpropagation Algorithm
Manajemen Mutu Perguruan Tinggi di Universitas Islam Negeri Syarif Hidayatullah Jakarta

This study examines the quality management of universities at the Syarif Hidayatullah State Islamic University Jakarta. In managing a university, it has its own uniqueness that manages knowledge as a college asset, so the focus of this research is the knowledge management implemented by Syarif Hidayatullah State Islamic University Jakarta? The method used in this study uses qualitative methods. The conclusion of this study is about the plan of Syarif Hidayatullah State Islamic University in Jakarta to implement knowledge management as its core business. However, it needs to be improved: increasing access to knowledge management units and increasing inventory of special collections consisting of historical knowledge manuscripts and archives as a source of knowledge needed by researchers and academicians. Syarif Hidayatullah Jakarta is headed for a World Class University, one program that needs to be made specifically is knowledge management that manages explicit knowledge and tacit knowledge. This program requires the human resources needed.
Peningkatan Kemampuan Berhitung 1-20 Melalui Penggunaan Media Corong Berhitung pada Siswa Kelompok B1 Taman Kanak-Kanak Muslimat Wonocolo Surabaya

This research is backgrounded by the low ability in counting 1-20 related to calculation and diminution. It is proven by the result of doing the enrichment exercises which was done by 20 students in a class but only 5 students who got BHS score (Berkembang Sesuai Harapan) in the indicator of mentioning calculation result. Therefore, the objective of this research is to know the use of funnel calculation media in order to increase the ability in counting 1-20 for the students of Kindergarten Muslimat Wonocolo Surabaya, and to know the raising ability in counting 1-20 by using the funnel calculation media related to calculation and diminution. The research design which is used in this research is action research by using Kurt Lewin model. It consists of pre-cycle, cycle I, cycle II and reflection. The participant of this research is 20 students of B-1 group at TK Muslimat Wonocolo Surabaya. The action research of Lewin Kurt model consists of 4 stages; planning, implementation, observation and reflection. The results of this research are: 1) The use of funnel calculation goes well in cycle I. It can be seen in the activity of the students which enthusiastic in using funnel calculation media. Besides, the observation result of the teachers and students get the score in the percentage of 63,09%. It also can be seen from the activity of the teachers and students which rises by getting the score of 79,76% with the increase in 6,65. 2) There is an increasing of the ability in calculating 1-20 which is proven by the raising of the score after using funnel calculating media in cycle I in amount of 63,74% and the cycle II in amount of 76,87% by the increasing in the percentage of 13,13.
PALEMBANG EXPLORE APPLICATION USING ANDROID

This research produced an Palembang Exlore application which is an application for tourism promotion in Palembang City. Tourism here is not only historical sites, but also can be other tours, including historical or famous places / buildings in a city, where you can buy souvenirs or souvenirs, where to buy special foods from a region or culinary, and so on. This application is useful for tourists, both domestic and foreign who will visit the city of Palembang. So that tourists are expected to know all the tourist attractions that can be visited, ranging from tourist places or historic buildings to culinary tours of the city of Palembang. The method used in making this application or software uses the Extreme Programming method which consists of several stages, namely planning, design, coding and testing. The application is made using HTML 5 programming language. This application is used through the Android operating system
A Causality Analysis for Nonlinear Classification Model with Self-Organizing Map and Locally Approximation to Linear Model

In terms of nonlinear machine learning classifier such as Deep Learning, machine-learning model is generally a black box which has issue not to be clear the causality among its output classification and input attributes. In this paper, we propose a causality analysis method with self-organizing map and locally approximation to linear model. In this method, self-organizing map generates the cluster of input data and local linear models for each node on the map provides explanation of the generated model. Applying this method to the member rank prediction model based on Deep Learning, we validated our proposed method.
Computer-aided detection using non-convolutional neural network Gaussian processes

Deep convolutional neural networks (CNNs) have in recent years achieved record-breaking performance on many image classification tasks and are therefore well-suited for computer aided detection (CAD). The need for uncertainty quantification for CAD motivates the need for a probabilistic framework for deep learning. The most well-known probabilistic neural network model is the Bayesian neural network (BNN), but BNNs are notoriously difficult to sample for large complex network architectures, and as such their use is restricted to small problems. It is known that the limit of BNNs as their widths increase toward infinity is a Gaussian process (GP), and there has been considerable research interest in these infinitely wide BNNs. Recently, this classic result has been extended to deep architectures in what is termed the neural network Gaussian process (NNGP) model. In this work, we implement an NNGP model and apply it to the ChestXRay14 dataset at the full resolution of 1024x1024 pixels. Even without any convolutional aspects to the network architecture and without any data augmentation, our five layer deep NNGP model outperforms other non-convolutional models and therefore helps to narrow the performance gap between non-convolutional and convolutional models. Our NNGP model is fully Bayesian and therefore offers uncertainty information through its predictive variance that can be used to formulate a predictive confidence measure. We show that the performance of the NNGP model is significantly boosted after low-confidence predictions are rejected, suggesting that convolution is most beneficial only for these low-confidence examples. Finally, our results indicate that an extremely large fully-connected neural network with appropriate regularization could perform as well as the NNGP if not for the computational bottleneck resulting from the large number of model parameters.
Specific Character of Professional Activity of the Conductor of the Academic Choir

The aim of the paper is to describe the specific phenomenon of art, which is organically linked to the human need to express the spiritual essence. Music has a special place among the arts and is combined with deep psycho-physiological reaction to the variety of sound environments. Research methodologyincludes the system approach to the specific professional creativity of choirmaster. The cultural approach raises the possibility of the sophisticated analysis of professional choral art and formation. Results. Interpretation as a special kind of activity in musical performance arose in the late 19th and 20th centuries. The real situation embodied in educational practice and performing basic principle — the unity of artistic and technical training in the theory and methodology of music and performing arts, is quite critical. For the general practice it is characterized by a lack of unity and integrity of music and art components and technology performance.From the standpoint of aesthetics the main goal art influence on personality is the formation of a creative approach to the perception of artistic values and aesthetic information contained in choral works.Novelty. The most difficult problem artistic, poetic aspects performance arts are not studied in modern science. These issues are musical expressive intonation, definitions of the style of the author and stylistic trends of the era, the construction of the composition of the work, its focus on the perception of the audience.The practical significance. Education of choirmaster and his artistic thinking is a complex, multi-faceted and multi-system process. Musical pedagogy has developed the concept of the relationship of arts in art education of the younger generation.Keywords: music culture, performing arts, performing musician, individual author’s features.
Natural and Artificial Intelligence in Consciousness Society.

Consciousness Society is characterized by equality of structured Natural Intelligence (NIstructured) and Artificial (AI) ROBO-Intelligence.The purpose of research constitutes adaptable algorithmic process of robotic implementation of Artificial, Robotic Intelligences (AI) elements; there are used Adaptable Tools as Technological information methodology basis.There are analyzed creative, emotional, temperamental, and sensual sets of items which are to be implemented in ROBO-intelligences.They represent one axe of robotic tables constituting first level of ROBO-intelligences elements.Another dimension of these tables represents items' evolution functions.Functions are located on other axe of robotic matrices.This second axe represents intellectual, emotional, sensual, and spiritual evolution steps.Using adaptable tools of algorithmic definitions of robotic elements are defined superior, next level elements of ROBO -intelligences.Presented adaptable information technology for ROBO-intelligence's creation process is used in the institutional project "Creating Consciousness Society" that is developed in the period 2008 -2018 by the team of AESM and supporters.
Remidiasi Miskonsepsi Siswa Pada Materi Listrik Dinamis Menggunakan Ebook Interaktif

Based on previous research, the student had many misconceptions occurred in dynamic electrical material so the researcher developed interactive ebook of dynamic electrical material which was integrated with PhET simulation software to reduce misconception on that material. The purposes of this study are: (1) Describe the validity of an interactive ebook based on expert assessment in terms of material, media, and language and three physics teachers; (2) Describe the effectiveness of interactive ebook based on the decrease of student misconception after learning with developed ebook; and (3) Describe the practicality of the ebook based on the student response questionnaire. The method used in ebook development refers to the Instructional Design Strategy developed by Moore &amp; Kearsley with the sequence: Analysis, Design, Development, Implementation, and Evaluations. The results of this study are: (1) Development of an interactive ebook is in a very decent category in terms of validity from expert assessment on material, media, and language ebook and three physics teachers; (2) The effectiveness of interactive ebook is in the effective category, it could reduce student misconceptions on dynamic electrical materials effectively; and (3) The developed ebook are very practical to use, responses of students were positively
TÉCNICA, DECISÕES E A CULTURA DE SEGURANÇA

âFor a successful technology, reality must take precedence over public relations, for nature cannot be fooled.â Richard Feynman [1]
Pengembangan Sistem Pencarian Pada Tujuh Kitab Hadis Menggunakan Algoritma Knuth-Morris-Pratt

Hadith search information system requires the main function that is the word search method to make it easier for users to find the word they are looking for. Word search can be conducted by using string matching algorithm to obtain the search term, one of them is Knuth-Morris-Pratt algorithm. This algorithm has two stages in the search process, namely the pre-KMP process which is the stage of giving a shift value in the keyword (pattern) and KMP-Search stage which is a matching phase between text and keyword (pattern). The process of matching text and patterns is conducted from the left to the right based on the value of the shift that has been obtained in the pre-KMP process. The search time is influenced by the length of the text on the database and the pattern the user is looking for, the longer the text and pattern, the search time will increase.
Retraction of Effects of the Application of Mobile Learning to Criminal Law Education on Learning Attitude and Learning Satisfaction

Original Article: EURASIA J. Math., Sci Tech. Ed (2018), 14(7), 3355–3362. https://doi.org/10.29333/ejmste/91730 This document states that the Article is retracted by request from the author.
A Note on some Sanskrit Words in the Japaneese Language

A Note on some Sanskrit Words in the Japaneese Language