Reviewerly/exHarmony huggingface dataset:
Producción científica sobre integración de TIC a la Educación Física: estudio bibliométrico en el periodo 1995-2017

espanolEn las dos ultimas decadas, la literatura ha aportado argumentos de forma sistematica sobre la utilidad de la integracion de las Tecnologias de la Informacion y la Comunicacion (TIC) en la Educacion Fisica. El objetivo de la presente investigacion es describir el comportamiento de la produccion cientifica en el area de las TIC y la Educacion Fisica en el periodo de 1995 a 2017. El estudio se basa en el analisis bibliometrico de publicaciones recopiladas en diversos repositorios de publicaciones cientificas. Se recolecto un total de n=521 contribuciones, que incluyen articulos cientificos, presentaciones en eventos cientificos, tesis, libros y capitulos de libros. Se determinan los autores mas productivos, las principales fuentes de informacion, las principales lineas de investigacion y las contribuciones mas influyentes. Se encuentra un alto grado de colaboracion nacional, un bajo nivel de colaboracion internacional y un limitado numero de autores con mas de una publicacion en el tema. En el analisis sobre la madurez del dominio se considera que estamos ante un dominio de conocimientos en fase de crecimiento. EnglishIn recent decades, scientific literature has provided arguments about the integration of Information and Communication Technologies (ICT) in Physical Education in a systematic way. The objective of this research is to describe the trend of scientific production in the area of ICT and Physical Education in the period from 1995 to 2017. The study is based on the bibliometric analysis of publications collected in various databases of scientific publications. A total of n = 521 contributions were collected, including scientific articles, presentations at scientific events, theses, books, and book chapters. The most productive authors, the main sources of information, the main areas of research, and the most influential contributions were determined. There is a high degree of national collaborations but a low level of international ones, and a low number of authors with more than one publication on the subject. In the domain maturity analysis, we can consider this topic as in a growth phase.
Feature Reduction of Short Text Classification by Using Bag of Words and Word Embedding

Text classification for data preprocessing methods regularly uses bagof-words (BoWs).In a large dataset, BoWs always include many vectors with very large sizes and high dimensions.The authors introduced a new data preprocessing method for feature reduction of short text classification, namely NDTMD.It reduces features of the dataset using BoWs and word embedding (WE), and can solve the weaknesses of BoWs.The experiment consisted of four steps: 1) 5 datasets were selected from the data science community website, Kaggle; 2) the new methods were compared with 5 commonly used data preprocessing methods and 4 of these 5 methods used the state of the art as their baseline, while the other one used BoWs.One of the new data preprocessing methods used features reduction of BoWs to produce a new document termed matrix data (NDTMD); 3) the authors generated many classification models by 3 classifiers: support vector machine, logistic regression, and convolutional neural network for text classification; and 4) the above classifiers were applied to each preprocessing dataset and evaluated using feature reduction rate (FRR), accuracy, kappa, and running time performance.The results showed that classification models had the highest performance when using NDTMD.In particular, classifier algorithms had the highest accuracy and kappa but the lowest running time.The new data preprocessing methods can be used to preprocess short text classification and also can be applied with real social media data.
A Cloud Services Security Analysis

The aim of the article is the analysis of cloud services and data stored into cloud infrastructure. At first, history and principles of cloud computing technology are introduced. This is flowed by the introduction of security threats related to the use of cloud computing technology for storing data into cloud infrastructure managed by a third-party subject, whose infrastructure is different from that of the owner of the stored data. Based on the identification of security threat identification, tools designated for encryption of data saved into cloud, and allowing for increased security and mitigation of threats related to cloud data storing are showcased. Furthermore, these tools are compared using a comparative analysis in terms of workload on system and network adapter resources while encrypting and storing the data into cloud. As part of the comparative analysis, a comparison of encryption and saving of a single 1-GB file and 10,000 .txt files was performed. In the last part of the article, the results of the comparative analysis are interpreted visually and with the description of the measured values.
An Anti-fake Bitmap Graphic Encoding and Decoding Method for Commodity Packaging

The paper is to enhance the angle of rotation and marking points as well as to increase the recover rate after random damage. We will make a redundant symmetric image and encode for every bit image, connecting to the raw data of commodity. The corresponding information is saved in data base for decoding and tracing back. Using the information of data base and the encoding rules, we could read the raw commodity data. At the same ink jet quantity, the method in the paper is better than the bit number and space availability.
Task Sensitivity in Continuous Electroencephalogram Person Authentication

This research investigates on the task sensitivity in multimodal stimulation task for continuous person authentication using the electroencephalogram (EEG) signals.Pattern analysis aims to train from historical examples for prediction on the unseen data.However, data trials in EEG stimulation consists of inseparable cognitive information that is difficult to ensure that the testing trials contain the cognitive information matching to the training data.Since the EEG signals are unique across individuals, we assume that multimodal stimulation task in EEG analysis is not sensitive in train-test data trials control.Data trial inconsistency during training and testing can still be used as biometrics to authenticate a person.The EEG signals were collected using the 10-20 systems from 20 healthy subjects.During data acquisition, subjects were asked to operate a computer and perform various computer-related tasks (e.g.: mouse click, mouse scrolling, keyboard typing, browsing, reading, video watching, music listening, playing computer games, and etc.) as their preferences, without interruption.Features extracted from Welch's estimated Power Spectral Density in different frequency bands were tested.The designed authentication approach computed intra-and inter-personal variability using Mahalanobis distance to authenticate subject.The proposed EEG continuous authentication approach has succeeded.Data collected from multimodal stimulus disregard of task sensitivity able to authenticate subject, where the highest verification performance shown in the low-Beta frequency band.Evidence found that effective frequency region on the middle band was anticipated due to the data collected was based on subject voluntary actions.Future research will focus on the effect of subject voluntary and involuntary actions on the effective frequency region.
Akuisisi Bukti Digital Aplikasi Viber Menggunakan Metode National Institute of Standards Technology (NIST)

The rapid development of mobile technology today is directly proportional to the development of mobile applications in it. Making it easier for people to choose and use the application as they want. This has resulted in misuse of negative things, ranging from human trafficking, drug trafficking, as well as online prostitution business. Viber is an Instant Messenger application that makes it easy for users. This application can be used to send messages, call, send photos, audio and video to others. This application has been used by 260 million people worldwide. This is the basis of research to acquire digital evidence in Viber applications. Data obtained after acquiring based on the work steps of NIST are the accounts of the perpetrators, contacts targeted by the perpetrators, call history, text messages, picture messages and videos.
If Anything on This Graphic Causes Confusion, Discard the Entire Product

Reading a visualization is often an experience mediated by people other than designers themselves. In more than two decades designing and teaching visualization, I have learned to embrace the mantra "what you design isn't what people see." It applies not only to visualizations, but to most artifacts, tools, and technologies.
Similarity Detection for Hadith of Fiqh of Women using Cosine Similarity and Boyer Moore Method

Nowadays, people can get information easily including about fiqh and hadith as a source of Islamic law.The problem is, there are so many articles about jurisprudence whose understanding refers to the laws or rules relating to the hadith whose validity cannot be ascertained.The study aims to determine the degree of similarity between the hadith contained in articles with reliable sources such as books and books.One of the outputs of this study is an application that can determine the similarity of hadith using Cosine Similarity and Boyer Moore by matching strings starting from the right position to the leftmost position and using the cosine similarity method to determine the similarity based on the calculation of the distance between vectors A and B that produce angles cosine x between the two vectors.In the testing phase, the proposed model can run as planned.In one test scenario, the number of keywords tested was 9 cases compared to the categories in the database with an accuracy of 80%.And determine the similarity of two or more objects Using the cosine similarity method with weights The percentage of similarity is proportional to the sample of words entered, which is equal to 36%.
Design Challenges of Trustworthy Artificial Intelligence Learning Systems

In the near future, more than two thirds of the world’s population is expected to be living in cities. In this interconnected world, data collection from various sensors is eased up and unavoidable. Handling the right data is an important factor for decision making and improving services. While at the same time keeping the right level of privacy for end users is crucial. This position paper discusses the necessary trade-off between privacy needs and data handling for the improvement of services. Pseudo-anonymization techniques have shown their limits and local computation and aggregation of data seems the way to go. To illustrate the opportunity, the case for a novel generation of clustering algorithms is made that implements a privacy by design approach. Preliminary results of such a clustering algorithm use case show that our approach exhibits a high degree of elasticity.
Simulated Data to Estimate Real Sensor Events—A Poisson-Regression-Based Modelling

Automatic detection and recognition of Activities of Daily Living (ADL) are crucial for providing effective care to frail older adults living alone. A step forward in addressing this challenge is the deployment of smart home sensors capturing the intrinsic nature of ADLs performed by these people. As the real-life scenario is characterized by a comprehensive range of ADLs and smart home layouts, deviations are expected in the number of sensor events per activity (SEPA), a variable often used for training activity recognition models. Such models, however, rely on the availability of suitable and representative data collection and is habitually expensive and resource-intensive. Simulation tools are an alternative for tackling these barriers; nonetheless, an ongoing challenge is their ability to generate synthetic data representing the real SEPA. Hence, this paper proposes the use of Poisson regression modelling for transforming simulated data in a better approximation of real SEPA. First, synthetic and real data were compared to verify the equivalence hypothesis. Then, several Poisson regression models were formulated for estimating real SEPA using simulated data. The outcomes revealed that real SEPA can be better approximated ( R pred 2 = 92.72 % ) if synthetic data is post-processed through Poisson regression incorporating dummy variables.
Wavelet Methods and Adaptive Grids in One-Dimensional Movable Boundary Problems

Adaptive wavelet collocation methods use wavelet transform and filtering to generate adaptive grids. However, if the boundary moves, the grid becomes aberrant. It baffles wavelet transform and makes the adaptive wavelet methods lose advantages on computational efficiency. This paper develops a series of methods or skills to effectively perform wavelet transform and to generate adaptive grids for one-dimensional movable boundary problems. The methods remain the original inner grid points and keep the grid in the original-nested structure, in order to remain scanty during the whole computing process. For boundary extending, the adaptive wavelet program begins to run on the very new grid beyond the original boundary once it reaches a nested structure, which is called the Intermittent Adaptive Method as a consequence. If the boundary extends tremendously, the new nested grids can be combined to a greater nested grid for further efficiency, which is named the Grid Combine Method. While for boundary contracting, a fictitious boundary is addressed to replace the original boundary that will recede, so wavelet transform can be successfully performed on the original nested grid. Finally, two numerical tests, local features moving and gas gun, were resolved and discussed to show the evolution process of the adaptive grids with the boundaries moving. For boundary contracting, the valid points decrease because the computation domain recedes; while for boundary extending, the valid point numbers vary between a range that almost remains unchanged.
Exploring Latent Information for Unsupervised Person Re-Identification by Discriminative Learning Networks

For unsupervised domain adaption in person re-identification (Re-ID) tasks, the generally used label estimation approaches simply use the global features or the uniform part features.They often neglect the variations of samples having the same identity caused by occlusion, misalignment and uncontrollable camera settings.In this paper, we propose a discriminative learning network with target domain latent information (LatentDLN) to enhance the generalization ability of the Re-ID model.Specifically, to generate a discriminative and robust representation, two types of latent information in the samples from the target domain are explored by the multi-branch deep structure.First, the key points based valid region information is used to leverage the local and global cues in human body, and then a heuristic distance metric learning method based on the global features and the local features is proposed to effectively evaluate the similarity between different images.Second, the camera style transferred images are used as augmentation data to bridge the gap between different cameras in target domains.Moreover, the re-rank mechanism based on reciprocal neighbors is designed to improve the quality of the label estimation.Experimental results on Market-1501, DukeMTMC-ReID and MSMT17 datasets validate the significant effectiveness of the proposed LatentDLN for unsupervised Re-ID.
Sistem Informasi Geografis (SIG) Pemetaan Kost-Kosan Menggunakan Metode Formula Haversine

Geographic Information System ia a geospatial software system that has the ability to build, store, manage and display geo-referenced information, for example data that is identified by location. By using GIS, it is expected that it will be easier for prospective students and students to find out the location of boarding houses that are located around the campus of Mulawarman University. The system development method uses the waterfall method. While the system design method uses UML (Unified Modelling Language) to visualize, determine, develop and document a software system. The algorithm used in this study uses the haversine formula which will later help to find the nearest boarding house location around the campus of Mulawarman University, the haversine formula will produce the shortest distance between two points, for example on a ball taken from the longitude and latitude. The result of this study will disply detailed boarding location information, besides that on this geograpihic information system the user will later be able to see the details of boarding and admin data can change, add data to the boarding owner and be technically responsible for the running of the application, while the boarding owner is only responsible on managing boarding data on their respective users.
Automatic Parameter Setting in Hough Circle Transform

The Hough circle transform has been widely used in pattern recognition to find circles in images. It, however, has many parameters to be adjusted before usage. This study focuses on the analysis of the circular size and distribution density for the images of ball maps in electronic parts. The amounts of projection of the binary conversion quality in different directions are calculated, and the parameters required in the Hough circle transform are automatically adjusted based on the amounts of projection. In this way, the time for setting blind tests could be reduced and the accuracy of pattern recognition could be improved.
Approaches to Text Analysis

Text Analysis is a broad term that covers many approaches and technologies. Those initially stemming from the academic sphere have come to enter the commercial, and today there is a wide interplay between the two. A further dichotomy is that between natural language and computational approaches. Over time, approaches have come to draw upon each other, although there are still clear dividing lines and practitioners tend to rely mainly on one approach or the other. This paper seeks to draw out these approaches and give an account of them over time. It also points to future developments where artificial intelligence is increasingly used.
Wavelet Codes and Their Implementation for Protection of NAND Flash Memory

Nowadays wavelet theory finds implementations in many scientific aspects. It is implemented in the signal processing such as video and audio signals, in data transformation, and in many other areas. In this work, we present implementations of wavelets in coding theory and then apply resulting codes for the protection of NAND flash memory. Our application with new wavelet codes and their implementation in NAND flash memory prevents different types of errors and gives a higher level of security.
Pentingnya budaya kolaboratif : suatu tinjauan literatur

At present, cooperation between organizations and within organizations is demanded that an organization be able to compete. In the educational environment, collaborative culture is considered as an important component in influencing overall school success. Based on a literature review, this article discusses the importance of collaborative culture in educational organizations as a strategy in increasing school effectiveness and increasing teacher capacity. This research shows that collaborative culture has an important role not only at the teacher and student level but also at the school level and ultimately will improve the quality of the school.
Providing Service Composition to Cyber-Physical System for Industrial Fault Detection

This paper presents an approach to providing service composition to cyber-physical system (CPS) for industrial fault detection and vibration detection in particular. While vibration fault detection has been increasingly adopted in industrial sectors and critical infrastructure for economical and safety concerns, architectural and performance restrictions of most systems in this area impose restrictions on its wide and flexible usage. Recent research shows that it is promising to applying service-oriented architecture to developing industrial systems. We regard that enhancing CPS with services and service composition schemes in industrial vibration fault detection be feasible and promising. The architecture of our vibration fault detection CPS system, consisting of the enterprise level, gateway level and endpoint level, is integrated with various vibration detection services at relevant levels. Service composition with mapping from physical services to virtual services and to composition services is designed. It is shown by testing results that the proposed approach makes the system for real-time vibration fault detection more flexible and effective.
Energy Efficient Quadcopter Drone Design using Design of Experiment (DOE) Method

This paper presents the results on the development of a quad copter drone and the application of Design of Experiment (DOE) to identify the best configuration of several key parts in the drone.The idea is to get the longest flight time with minimum energy consumption (battery usage).The drone is assembled in house by the researcher by using hobby grade Arduino based microcomputer and the analysis of DOE uses 23 factorial designs with 2 replications.The results of the study is determined by identifying setup that produces lowest voltage drop that represents minimum usage of battery power.From the experiment, we conclude that optimal design will yield minimum voltage drop that reflects to high efficiency of power usage.
Digital Data Classification and Extraction for Records Management of PAPS and PACS Documents

The Department of Social Welfare and Development -Adoption Resource and Referral Unit is in need of emerging technologies to store records of the Alternate Parental Care program.A technology that would digitize data, case visualize and notify managers and Server-Based digital storage.To hasten the storing process, the system does the classification and extraction of data from a PDF document using Tesseract Optical Character Recognition (OCR).OCR extracts the text from an image by converting the whole image into binary pixels and from binary pixels and compare the recognized sets to its library to predict the text and set of words.It uses Keras to train the model with tensorflow on the backend to classify data.Keras works by defining a sequence of layers in a network by creating a sequential class and adding new layers.This will be done by creating an array of layers and pasting it to the constructor of the sequential model.The researchers produced 4 four documents with ten pages of the same content in different resolutions.Based on the result gathered, 75 DPI resolution has an accuracy percentage of 94.8548778, for 150 DPI is 99.23619895, while 98.91023618 for 300 DPI and 98.7416335 for word application generated document.For 75 DPI, the error contains almost English words, while in 150 DPI and 300 DPI the error usually came from punctuation marks and in word application generated document, the error usually came from a capitalized letter.
Fast, Accurate Vehicle Detection and Distance Estimation

A large number of people suffered from traffic accidents each year, so people pay more attention to traffic safety.However, the traditional methods use laser sensors to calculate the vehicle distance at a very high cost.In this paper, we propose a method based on deep learning to calculate the vehicle distance with a monocular camera.Our method is inexpensive and quite convenient to deploy on the mobile platforms.This paper makes two contributions.First, based on Light-Head RCNN, we propose a new vehicle detection framework called Light-Car Detection which can be used on the mobile platforms.Second, the planar homography of projective geometry is used to calculate the distance between the camera and the vehicles ahead.The results show that our detection system achieves 13FPS detection speed and 60.0% mAP on the Adreno 530 GPU of Samsung Galaxy S7, while only requires 7.1MB of storage space.Compared with the methods existed, the proposed method achieves a better performance.