Reviewerly/exHarmony huggingface dataset:
Sensor-based physical activity monitoring: Application of machine learning approaches

Long-lived and healthy lifestyles are the means for sustainable physical and mental wellbeing. Physical activity monitoring is one of the key aspects of maintaining a healthy lifestyle. It can be achieved with the help of widely used smartphones containing accelerometers sensors. The current study proposes the applicability of different machine learning methods for physical activity monitoring based on accelerometer sensor data and their classification. In this paper, Radial Basis Function network (RBF), Multilayer Perceptron (MLP), K-nearest neighbors classifier (KNN) and Random Forest decision tree (RFDT) have been employed for the classification task. Among the classification algorithms, RFDT and KNN recognize all activities very well (97.5% and 96.8%, respectively) with less confusion than other algorithms. Based on accuracy and error scores, it is found that RFDT with the lowest root-mean-square error (0.0758) produce better outcomes than other algorithms. This study observed that RFDT has an important role in classifying the physical activities with better accuracy within a short span of time. Further investigation will be carried out to find out the correlation of physical activity monitoring with different diseases.
Infectious Disease Expert System Using Dempster Shafers With Recommendations for Health Services

Delay in the handling of a type of disease can pose a risk for someone who has the surrounding environment. Often the casualties are caused by people's ignorance of the spread of dangerous infectious diseases. People's ignorance as an action that must be done immediately and where to do to get help. Thus it is necessary to build an application of an expert system that can diagnose infectious diseases, provide recommendations for disease management, and provide recommendations for appropriate and acceptable health services. The system was built to diagnose six types of infectious diseases that are of particular concern to Malang City. Various infectious diseases with similar symptoms that appear will lead to the possibility of a diagnosis and many possibilities for diagnosis. The Dempster Shafer method is an approved one that can be used in overcoming these factors. The disease expert consultation system application using the Dempster Shafer method obtained an accuracy test result of 88.5%. While the system usability test obtained results, 76% agreed to system reliability, 85% strongly agreed to system efficiency, 83% strongly agreed to ease for use system, and 79% agreed to accurate system.&#x0D;
3D Smith Chart's Extensions and Expanding

Some extensions on the 3D Smith Chart are made: constant reflection coefficient magnitude and phase circles, normalized impedance magnitude and phase (quality factor) circles, stability circles, unilateral power gain circles, operating and available power gain circles and noise figure circles. To make an actual 3D Smith Chart, a method of expanding the 3D surface to a 2D one is proposed based on the theory of spherical surface expanding. Pasting the printed expanded curves to a ball, the 3D Smith in reality is done. The method of making the actual 3D Smith Chart is easy, fast and low cost and can be used in teaching and designing conveniently.
The Legal Search in Criminal Procedure of Scientific Verification Method for Securing Various Digital Evidence Admissibility

2016년 05월 29일, 형사소송법의 개정으로 인하여 디지털 증거파일의 작성자를 특정하는 과학적·기술적 진정성립의 증명방법이 매우 중요하게 되었다. 즉, 이에 따라 과학적·기술적 방법으로도 디지털 증거파일에 대한 작성자 특정의 진정성립을 증명할 수 있는 길이 열리게 되었으므로, 이제는 그 진정성립을 인정하기 위해서 어떤 방법으로 어느 정도의 증명을 해야 하는 것인지가 매우 중요한 문제로 대두되었다고 하겠다. 본고는, 이러한 디지털 전문증거의 진정성립에 대한 과학적·기술적 증명방법의 중요성과 필요성에 따라 분석의 대상을, (1) 파일이 저장되어 있는 시스템에 관한 정보§(a)·(b), (2) 대상파일 자체에 관한 정보§(d)·(e), (3) 대상파일과 동일한 기기에 저장되어 있는 주변파일에 관한 정보§(c), (4) 네트워크 접속 및 이용에 관한 정보§(a)~(e)로 구분하였고, 또한 유형화된 각각의 분석대상에서 추출할 수 있는 정보를 검토한 뒤, 그 관련정보 중 각종 디지털 증거파일의 작성자를 특정할 수 있는 형사소송법 제313조 제2항의 객관적 기준 및 합리적 방안을 모색하였다.On May 29, 2016 criminal procedure act was amended which made verification method of establishing scientific·technical authenticity that specifies a person who makes out digital evidence file very important. As it becomes possible to verify establishment of authenticity of a person who makes out digital evidence file with scientific·technical methods, it becomes very important that what methods should be used and how much verification should be made to recognize the establishment of authenticity. This study classified the targets of analysis according to importance and need of scientific·technical verification methods for establishment of authenticity of digital hearsay evidence into (1) information on system in which files are saved §(a)·(b), (2) information on target file itself §(d)·(e), (3) information on peripheral files which are saved in the same device with target file §(c), and (4) information on network access and use §(a)~(e) and examined information that can be extracted from each analysis target and searched for objective standard and reasonable methods that can specify a person who makes out digital evidence file among information.
TopicInk: Visualizing Disaster-Related Textual Data Using LDA Topic Modeling: Vast Challenge 2019: Honorable Mention for Clear Articulation of Methodology

We proposed a visual analytics tool to analyze social media posts through machine-learning techniques. Latent Dirichlet Allocation and Named Entities Recognition were used to extract semantic information. 12 topics were identified to interpret semantic meanings and reveal spatiotemporal patterns in the dataset. Our visualization consists of topic bubbles, frequency bar chart, stream graph, fisheye list, massage view, map view, word cloud, and social network graph. All the views are linked together and enhanced by efficient interactions. This paper describes the methodology and visualization design in detail.
Characterizing Knowledge Utilization during Software Design Process Using Pkami Model

Abundant of studies and intellectual efforts have been invested particularly in determining the influencing and inhibiting factors towards effective knowledge transfer. The intriguing aspects of knowledge transfer have enabled it to be studied and examined from diverse angles and multi perspectives. Many however, tend to overlook the essence of effective knowledge transfer that is, the utilization of knowledge being transferred. For knowledge-intensive environment such as software development project, knowledge integration which encompasses activities of transferring various knowledge across different software processes often takes place. Best case scenario would be a generous opportunity to learn from each other, creating new knowledge and ultimately delivering quality software. But many failed to reap its advantage resultant from its impulsive nature and lack of methods to verify use of knowledge when the transfer happens. Alarmed by this situation, we proposed PKAMI, a model for characterizing knowledge utilization thus enables the verification of effective knowledge transfer. In our previous study we focused into software architecture development. In this paper, we attempt to investigate knowledge transfer a step further, which is in the process of designing the software to be developed for a project, carried out by our students and supervised by our industrial partners. Our aim is to determine the occurrence of effective knowledge transfer by characterizing the knowledge use during software design process. We believe that our effort put forth in this research would be an extremely significant contribution to software engineering as well as knowledge management research.
Refined Neighbor Mean Interpolation Algorithm for Reversible Data-Hiding Techniques

Interpolation is the process of estimating the value of a function based on its neighborhood. Data Hiding is the technique of masking the presence of the data so as to prevent unauthorized user to detect its presence. Data hiding can be irreversible or reversible. In reversible data hiding, the original object can be restored after extraction of the inserted data. Reversible Data Hiding techniques based on interpolation have been explored greatly in the last decade. These methods have two main parts (i) interpolation algorithm so as to generate a cover image and (ii) the embedding algorithm that is used to embed the secret data in the generated cover image. In this paper, an improved method for interpolation of the images so as to implement a reversible data hiding is presented. The proposed method produces a visually similar image to that of the original image. The performance of the proposed algorithm is better than the methods available in the literature.
Grammaticalizzazione, costruzioni e frasi commento in italiano parlato: uno studio empirico

The aim of the paper is to analyse a set of discourse markers from the perspective of construction grammar showing that, despite their similarity, the two markers guarda 'look' and senti 'listen' seem to specialise into different patterns, or constructions, the latter being treated as the output of conventionalisation of structured pairs of form and meaning aspects. 'Guarda' occurs more frequently in argumenative discourse, whereas 'senti' occurs in genuine interactional contexts (attention-getting) and in sequential contexts (such as opening-boundaries in discourse prefacing answers). The two markers belong to different constructions on a global discourse level. Specific meaning aspects are contributed by the co(n)text.
A reversible steganography using prediction value coding and histogram shifting

Steganography aims to embed the secret information in digital media for the purpose of secret communication, so that embedded data is not visible. The reversible steganography ensures that image is completely recovered to its original form after the secret data is extracted out. We are implementing reversible steganography that combines linear prediction error value coding and histogram shifting.The cover image is divided into multiple blocks. The above mentioned methods are applied for each block of image. Linear prediction error coding method calculates the prediction error values of cover image using basic pixel by scanning image blocks in inverse S-order. Histogram is generated for prediction error values to find the two peak points and two zero points. Histogram shifting method embeds the secret data in peak points of histogram of image. The reverse linear prediction error calculated to obtain stego image. The extraction and recovery procedure are done to extract secret message and recover the cover image. In the experimental results the better hiding capacity is obtained for smaller block size with fractional improvement to image quality. Keywords: Steganography, Reversible data hiding, Inverse S-order, Histogram shifting.
A Chinese Oral Question-and-Answering System Based on LSTM

We have developed a new answering system, which recognize questions inputs in natural language and respond accordingly. We implement a deep learning method to understand conversation, dialogue and sort out a summary of narrative. Many papers have already shown how to combine and apply various tools for similar problems, however, only few of them mentioned how to effectively reduce the error rate of speech recognition and combine this part to answering system. In this paper, we combine these two functional parts and minimize the size of the model, which does not influence the accuracy of it. This model has been implemented in embedded system.
An Implications through the Analysis of Appreciation Sections and Activities in Secondary Music Textbooks

본 연구는 청각예술로 간주되는 음악에서의 기본적인 활동인 감상이 학교수업에서는 어떻게 수업으로 구체화되고 있는지에 관한 실태파악을 위한 기초연구로, 2015 개정 음악과 교육과정을 반영한 중등음악교과서의 감상제재곡과 학습목표, 활동을 살펴보았다. 이러한 중학교 음악 감상 제재곡 분석을 통하여 학습목표와 이를 성취하기 위한 활동의 연계를 살펴보고 효율적인 감상수업을 위한 시사점을 도출하고자 하는 것이 연구의 주목적이라 할 수 있다. 이를 위하여 첫째, 음악감상활동이 수행되는 학교 음악 수업의 기준이라 할 수 있는 음악과 교육과정에서의 감상영역의 내용을 살펴보고 둘째, 2015 개정 음악과 교육과정이 적용된 14종의 음악교과서를 분석하고, 마지막으로 효율적인 감상수업을 위한 논의를 덧붙이고자 한다.This study was a basic study on how appreciation, a basic activity in music regarded as auditory arts, is being shaped into a class in school classes, and looked at the appreciation sanctions, learning goals and activities of secondary music textbooks reflecting the revised music and curriculum of 2015. The main purpose of the study is to examine the link between the learning goals and the activities to achieve them through the analysis of these middle school music appreciation songs and to draw suggestions for efficient listening classes. To this end, we will examine the contents of the music and education curriculum, which is the standard for music listening activities, and analyze 14 music textbooks that are applied with the revised music and curriculum in 2015, and finally add discussions for efficient listening classes.
Centennial Anniversary of the March First Independence Movement and Role of Local Public Government Museum - Focusing on Yeoju Museum’s Case -

2019년은 3·1운동 100주년을 맞이하여 3·1운동의 역사를 정리하고 기억하는 시간이었다. 여러 박물관들이 전시를 통해 3·1운동의 역사를 국민에게 알리고자 노력하였다. 기초지자체 공립박물관들도 대중의 관심도가 떨어지는 지역 3·1운동 역사에 대한 연구와 전시를 통해 지역 3·1운동을 지역민들에게 알리고자 하였다. 그러나 기초자제체 공립박물관의 학예연구 인력의 부족과 전시에 집중할 수 없는 업무환경, 근대사 부분 전공 학예연구 인력의 미비로 인한 전시 주제에 대한 접근의 어려움은 지역 3·1운동 관련 전시를 수행하기 어렵게 하는 요소이다. 그런 이유로 소수의 기초지자체 공립박물관만이 지역 3·1운동 관련 전시를 수행할 수 있었다. 경기도 기초지자체 공립박물관 중 지역 3·1운동 전시를 수행해 낸 여주박물관의 사례를 통해 지역 3·1운동을 기념하고 전시하기 위해 어떠한 과정을 거쳤는지를 이 글에서 검토해 보았다. 여주박물관은 지역 3·1운동에 대한 자료 확보 등을 통해 3·1운동 역사를 정리하여 관련 연구를 새롭게 진행하였다. 이후 연구된 성과는 전시를 통해 지역민과 관람객들에게 여주 3·1운동을 알릴 수 있었다. 그리고 전시내용을 교육·체험·심화강좌·현장 답사 프로그램 활용하여 지역민과 관람객에게 전시내용의 내재화를 추구하였다. 전시와 일련의 프로그램을 통해 지역민들과 관람객들이 기존에 알지 못했던 여주 3·1운동에 대해 관심을 갖게 되었고, 이를 우리지역의 역사 나아가 나와 관련된 역사로 인식하게 되었다는 점이 이번 전시의 의의이다. 이번 3·1운동 100주년 기념전시는 지역 3·1운동을 정리하고 이를 보여주는 과정에서 기초지자체 박물관의 역량을 향상 시킬 수 있는 기회였다. 나아가 기초지자체 공립박물관이 지역 근현대사 자료를 수집·연구하여 전시를 통해 이를 지역민에게 전달할 수 있는 역량을 쌓는다면, 지역사회가 요구하는 박물관으로서의 역할을 할 수 있을 것이다.2019 was time to remember and organize the history of March First Independence Movement which was the hundredth anniversary. Many museums t ried t o let people know t he h ist ory of March F irst Independence Movement through holding special exhibitions. Local public government museums were also tried to let residents know the local March First Independence Movement which was indifferent. Local public government museum’s research manpower shortage, inaccessibleness of exhibitions topic and working environment which was could not concentrate on exhibitions was in trouble holding local March First Independence M ovement exhibit oins. Accordingly, a f ew l ocal p ublic government museums could hold a local March First Independence Movement exhibition. Yeoju Museum is one of the Gyeonggi province local public museums that could hold a local March First Independence Movement exhibition. Focusing on Yeoju Museum’s exhibition case, we could review the process of how local public museums remember a nd e xhibit local M arch F irst Independence Movement in this article. Yeoju Museum newly researched history of local March First Independence Movement through securing March First Independence Movement history materials of Yeoju. After this research, Yeoju Museum could newly let people know Yeoju March First Independence Movement through a special exhibition. Moreover, Yeoju Museum pursued the internalization of exhibition contents for residents and audiences by utilizing educations, experiences, deepen lectures, explore sites. Residents and audience become interested in Yeoju March First Independence Movement through a special exhibition and many programs are the importance of this exhibition. This March First Independence Movement exhibition is a chance to improve local public museum’s capability through organizing and exhibiting local March First Independence Movement. Furthermore, if local public museums could accumulate the capability to collect and research local modern history materials, local public museums will do a role that local community demands.
Camera Model Anonymisation with Augmented cGANs

The model of camera that was used to capture a particular photographic image (model attribution) can be inferred from model-specific artefacts present within the image. Typically these artefacts are found in high-frequency pixel patterns, rather than image content. Model anonymisation is the process of transforming these artefacts such that the apparent capture model is changed. Improved methods for attribution and anonymisation are important for improving digital forensics, and understanding its limits. Through conditional adversarial training, we present an approach for learning these transformations. Significantly, we augment the objective with the losses from pre-trained auxiliary model attribution classifiers that constrain the generator to not only synthesise discriminative high-frequency artefacts, but also salient image-based artefacts lost during image content suppression. Quantitative comparisons against a recent representative approach demonstrate the efficacy of our framework in a non-interactive black-box setting.
Enhanced bitcoin with two-factor authentication

Bitcoin transactions rely on digital signatures to prove the ownership of bitcoin. The private signing key of the bitcoin owner is the key component to enable a bitcoin transaction. If the signing key of a bitcoin is stolen, the theft who possesses the key can make a transaction of the bitcoin. In this paper, based on the distance-based encryption (DBE), we propose an enhanced version of bitcoin in order to protect the signing key. Our approach is based on our two-factor authentication, where the signing key cannot be retrieved without being identified via the password and biometric authentication scheme, and the user is only required to enter his password and fingerprint (or other biometric information such as a factual image) to retrieve the key. By doing this, we can effectively improve the bitcoin security and provide stronger authentication. An attractive feature of our scheme is that one of encryption schemes is asymmetric, in the sense that the decryption key (biometric information) is not stored in the device. We also provide the security model and proof to justify the security of our scheme.
Enhancing an attack to DSA schemes

In this paper, we improve the theoretical background of the attacks on the DSA schemes of a previous paper, and we present some new more practical attacks.
Facial Age Estimation based on Discrete Wavelet Transform- Deep Convolutional Neural Networks

Facial age estimation based on discrete-wavelet-transform deep convolutional neural networks (DWT-DCNN) is a biometric application based on deep learning. Facial age estimation obtains the range of ages of anonymous by taking his/her face images. Deep learning could be the most promising classification/ regression method for a decade. Almost all deep learning architectures including deep convolutional neural networks (DCNNs) cost millions of parameters and large time on training. With the aid of DWT-DCNN, the training period can be reduced, and the number of parameters could drop in some circumstances. Moreover, the experimental result indicates the relationship between DCNNs and traditional edge detection methods can be discovered. Adience has been chosen as the benchmarks.
TEAMWORK IN THE INTERNSHIP MOVIE DIRECTED BY SHAWN LEVY

Literature is one of the works which involves a lot of the human life aspects within itself. It is a tool used by various writers throughout time to convey messages figuratively. There are poetry, drama, prose, nonfiction, and media. The media is the newest type of literature genre that was created to encompass many new and important kinds of texts in todayâ€™s society, which includes movies, websites, commercials, billboards, and radio programs. The movie particularly caught the writerâ€™s interests as it focuses on life aspects that are important in human life. One of the aspects that the writer is interested in analyzing is about the teamwork that happened between the main characters of the movie, as well as the type of teamwork performed by them, and what effects it had on them .
The Jisc National Bibliographic Knowledgebase and Library Hub Discover & Compare and Cataloguing

Introduction The National Bibliographic Knowledgebase (NBK) is a merged database of library catalogues, drawn from university, specialist, and national libraries across the UK, plus Trinity College Dublin. It is being developed and run by Jisc (https://www.jisc.ac.uk/), a membership organisation who provide digital solutions for UK education and research, working with OCLC. The NBK aims to bring together the catalogues of all Higher Education libraries in the UK, along with many specialist re...
Combination of the Local Binary Pattern Histogram Method and SHA256 Bit in the Face Recognition System

Recognition face technology is very fast at this time, there are many face recognition applications that have been applied to devices such as smartphones, time attendance machines, room access permits, location surveillance, and others. There are a lot of weaknesses in facial recognition so that implementation is needed so that it is not easily hacked with the local binary pattern histogram and SHA256 bit methods in a face recognition system that uses a webcam in realtime by combining the two methods. From the results of facial recognition can be recognized by someone's face in real time with good accuracy results.
Modeling of Big Data Database Based on Agricultural Basic Geographic Information

Supported by existing network facilities and based on agricultural geospatial information resources, a large data database of agricultural geographic information was designed to build a unified agricultural geographic information platform with strong openness and expansibility. The platform includes soil testing formula fertilization management module, cultivated land resource management module, agricultural disaster control module, agricultural regional layout management module, agricultural situation and production management module, agricultural construction achievement display module, operation and maintenance management module, etc.
Secure Hashing Algorithms and Their Comparison

A secure hashing algorithm abbreviated as SHA. SHA uses methodologies similar to those used in MD4 and MD5 to create a cryptic message but has a more complex design. Due to its intricate and conservative design, SHA is cryptographically far more ahead in the race in comparison to its predecessors, i.e. MD4 and MD5 making one of its variants to be used in crypto currency transactions. This research paper analyses different SHAs based on various factors and check if one of them could be broken down with the help of backtracking.
Real-time semantics based plane object tracking for augmented reality

In this paper we present an application solution for real-time augmented reality. We achieve almost 30 frames per second on our device and maintained good result for augmented. We use textured planar object as target. Consider of the computational complexity, we use patch feature and ZSSD template matching method for point matching. In the meantime, we maintain a database of the target template as semantics information. The semantics includes multiple key frame images of target object in different position. With this semantic database, we figure out the problems caused by viewport change and achieve robust performance.