Reviewerly/exHarmony huggingface dataset:
오디오 기반 vs. 비디오 기반 영어 듣기평가 비교 연구

This study aimed to investigate whether or not there is a difference in Korean high school students’performance between traditional, audio-only method and video method for listening tests. The rationale for this study stems from the fact that while traditional listening tests still use audio-only method, language learners are presented with not only audio but also visual input in typical target language use (TLU) domains where acts of listening take place. An intact group comparison design, that is, a pre and post-test between groups design, was employed in this study. After confirming the homogeneity of the students in both groups in their listening ability through the pre-test, the test scores of one group (an audio-only group) and those of the other group (a video group) were compared through the post-test. After the post-test, the students in both groups were asked to complete a survey questionnaire in order to further explore various issues involving audio and video-mediated listening tests. The results showed that the students who took the video listening test performed better compared with those who took the audio-only test, and the difference in their test scores turned out to be statistically significant. The implications of these results on the construct of listening ability were discussed.
The Effects of Satisfaction in Major on Career Preparation Behavior and Career Decision Level : Focusing on the University Students Majoring in Airline Service

In this study, the effects of major satisfaction on career preparation behavior and career decision-making level were analyzed. For the sample, the valid samples of 241 were used for the empirical analysis. The analysis results of this study was analyzed using statistical package of SPSS for Window Version 20.0. The results of the hypothesis test were as follows: First, the relationship satisfaction had a significant effect on the information gathering activities and the tool provision activities, while the subject satisfaction and social awareness had an effect on information collection and practical efforts. Second, as a result of verifying the effect of major satisfaction on career decision level, relationship satisfaction, curriculum satisfaction, and social awareness satisfaction were shown in the order. Third, the effect of career readiness on the level of career decision was found to be the information gathering activity on the level of career decision. In this study, it is significant that the students of aviation service major suggested practical implications for improving career preparation behavior and career decision-making.
On Prover-Efficient Public-Coin Emulation of Interactive Proofs.

A central question in the study of interactive proofs is the relationship between private-coin proofs, where the verifier is allowed to hide its randomness from the prover, and public-coin proofs, where the verifier’s random coins are sent to the prover. The seminal work of Goldwasser and Sipser [STOC 1986] showed how to transform private-coin proofs into public-coin ones. However, their transformation incurs a super-polynomial blowup in the running time of the honest prover.In this work, we study transformations from private-coin proofs to public-coin proofs that preserve (up to polynomial factors) the running time of the prover. We re-consider this question in light of the emergence of doubly-efficient interactive proofs, where the honest prover is required to run in polynomial time and the verifier should run in near-linear time. Can every private-coin doubly-efficient interactive proof be transformed into a public-coin doubly-efficient proof? Adapting a result of Vadhan [STOC 2000], we show that, assuming one-way functions exist, there is no general-purpose black-box private-coin to public-coin transformation for doubly-efficient interactive proofs.Our main result is a loose converse: if (auxiliary-input infinitely-often) one-way functions do not exist, then there exists a general-purpose efficiency-preserving transformation. To prove this result, we show a general condition that suffices for transforming a doubly-efficient private coin protocol: every such protocol induces an efficiently computable function, such that if this function is efficiently invertible (in the sense of one-way functions), then the proof can be efficiently transformed into a public-coin proof system with a polynomial-time honest prover. This result motivates a study of other general conditions that allow for efficiency-preserving private to public coin transformations. We identify an additional (incomparable) condition to that used in our main result. This condition allows for transforming any private coin interactive proof where (roughly) it is possible to efficiently approximate the number of verifier coins consistent with a partial transcript. This allows for transforming any constant-round interactive proof that has this property (even if it is not doubly-efficient). We demonstrate the applicability of this final result by using it to transform a private-coin protocol of Rothblum, Vadhan and Wigderson [STOC 2013], obtaining a doubly-efficient public-coin protocol for verifying that a given graph is close to bipartite in a setting for which such a protocol was not previously known.
Task-Assisted Domain Adaptation with Anchor Tasks

Some tasks, such as surface normals or single-view depth estimation, require per-pixel ground truth that is difficult to obtain on real images but easy to obtain on synthetic. However, models learned on synthetic images often do not generalize well to real images due to the domain shift. Our key idea to improve domain adaptation is to introduce a separate anchor task (such as facial landmarks) whose annotations can be obtained at no cost or are already available on both synthetic and real datasets. To further leverage the implicit relationship between the anchor and main tasks, we apply our \freeze technique that learns the cross-task guidance on the source domain with the final network layers, and use it on the target domain. We evaluate our methods on surface normal estimation on two pairs of datasets (indoor scenes and faces) with two kinds of anchor tasks (semantic segmentation and facial landmarks). We show that blindly applying domain adaptation or training the auxiliary task on only one domain may hurt performance, while using anchor tasks on both domains is better behaved. Our \freeze technique outperforms competing approaches, reaching performance in facial images on par with a recently popular surface normal estimation method using shape from shading domain knowledge.
An improved view registration method and its application in laser imaging measurements

View registration (VR) is a procedure that determines the orientations and locations in a given coordinate system based on images captured by one or more cameras. Existing VR procedures typically rely on a set of images captured on a fixed calibration target (referred to as FVM, fixed view method, hereafter). This work reports the development and application of a new view registration procedure, referred to as the variable view method (VVM). The VVM procedure relies on a set of images taken on a calibration target at various orientations and/or distances. As shown in this work, both numerically and experimentally, with a set of carefully selected views, the VVM can significantly improve the VR accuracy compared to the FVM. Such enhanced accuracy is expected to benefit a range of applications, and its potential to improve the accuracy of common laser imaging measurements are discussed.
An Effective Fuzzy Neural Network with Reinforcement Learning Approach for Medical Data Classification

Nowadays, several researchers are facing challenges on the prediction of diseases from the huge volume of medical databases.So, researchers are using data mining techniques like association rules, classification and clustering to address challenges.The physicians make the right decisions for successful diagnosis of various diseases by using the prediction.The existing work classifies the data to predict the certain diseases, but still it faces the difficulties due to overfitting in the training data.The main aim of this research work is to classify the Medical Data (MD) by developing the feature selection based approach in MD Classification as MDC.The irrelevant features are eliminated from the MD by using Recursive Feature Elimination (RFE) method, then ranked the features to reduce the computation cost of the proposed method.The ranked features from the RFE are given as input to the Fuzzy Neural Network (FNN) with Reinforcement Learning (RL), which is used for classification.The proposed RFE-FNN method has the accuracy of the 98.57%, 98.15% sensitivity, 98.64% specificity and 95.47% F-Measure in Heart disease dataset.
On selection of optimal stop position and spatial orientation of mobile robot

Abstract The paper analyses the problem of finding optimal coordinates of a mobile robot equipped with a manipulator. An optimization criterion is proposed and validated, and a method for calculating most rational coordinates of the robot is described.
Constitutional Study on the Personnel Hearing of the National Assembly and an Investigation by the Procurator

2000년 국회법이 개정되고 인사청문회법이 제정되어 주요 공직후보자 등에 대하여 국회가 인사청문회를 실시하여 오고 있다. 국회의 인사청문회는 고위 공직자가 될 사람에 대하여 국회가 그 자질과 능력을 공직에 임명되기 전에 검증하기 위하여 당사자로부터 진술과 의견 등을 청취하고 필요한 경우 증인이나 감정인 및 참고인으로부터 증언이나 진술을 듣고 증거를 채택하는 제도이다. 국회의 인사청문권은 국회가 국정통제권의 하나로 고위공직자 등에 대하여 자질과 능력을 검증하는 것이라 할 수 있다. 따라서 자질이나 능력 혹은 도덕성까지도 검증을 하는 것이라 할 수 있다. 반면에 검찰의 검찰권 행사는 행정권의 하나로 수사를 통하여 범죄 혐의 유무를 명백히 하여 공소제기 여부와 증거 수집이나 보전 등을 위한 것이라 할 수 있고, 경우에 따라서는 영장청구를 통하여 이를 하기도 한다. 검찰의 검찰권 행사는 행정권의 일종으로 국회의 인사청문권과는 구별되는 것으로 검찰권과 국회의 인사청문권은 의의와 기능 등에서 차이가 있다. 권력분립에 근거하여 국회는 국정통제권을 행사하는 권한 가운데 하나가 인사청문권이라 할 수 있고, 검찰의 검찰권은 행정권 행사의 하나인 것이다. 따라서 공직후보자에 대하여 국회의 인사청문회 도중에 검찰이 공직후보자에 대하여 수사를 하고 혹은 이와 관련하여 검사가 영장을 청구하고 법원이 영장을 발부한다고 하여, 검찰이나 법원이 국회의 권한을 침해한다고 볼 수 없고 검찰의 검찰권과 국회의 인사청문권이 충돌되는 것이라 할 수 없다.The Parliament Act was revised in 2000 and the Law on personnel Hearings was promulgated, and Parliament held personnel hearings for key candidates for public office. The Personnel Hearing is conducted taking into account the statements and opinions of the parties to verify the qualifications and capabilities of senior officials prior to their appointment to public positions. This system uses evidence by hearing testimony and statements from witnesses, evaluators and witnesses. The Personnel Hearing of the National Assembly can be said to be that Parliament verifies the qualities and abilities of senior officials as the right of government control. Therefore, it can be said that qualities, abilities or morals are also verified. The compentence of prosecutor may be used to investigate whether crimes are suspected by the prosecution as an administrative authority, to institute criminal proceedings, and to gather and keep evidence. Sometimes this is done through. The compentence of prosecutor to criminal prosecution is a kind of administrative power separate from the personnel hearing parliament. With respect to a candidate for a public office, at the personnel hearing, the prosecutor investigates the candidate or in this regard, the inspection requests a warrant and the court issues a warrant. Prosecutors and courts can not be considered a violation of Parliament s powers and there is no conflict between the competence of prosecutor to prosecute and the parliamentary personnel hearing
Affleck, Ada C - Biographical entry - Index to the AMA archive

Affleck, Ada C - Biographical entry - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
RDB2OWL: A Language for Database to OWL Mapping and its Implementation

Most data in industry still resides in relational databases (RDB) but Semantic web uses standard RDF and OWL formats.We consider a previously developed mapping language RDB2OWL allowing compact and end-user readable mapping specification.We describe the RDB2OWL implementation by translation into R2RML standard language that avoids the view rowset multiplication due to several 1-to-n relations from a single class in the ontology.
Performance Evaluation of Pontianak Kapuas Indah Market from Architecture and Behaviour Aspect

The Government of Pontianak City efforts in carrying out the mission of creating quality and representative urban infrastructure are a program to improve and assets development of public facilities. It formed of infrastructure and are currently functioning for public service facilities. One of the assets of this public facility is the 40-years-old Pontianak Kapuas Indah Market, located right on the edge of the Kapuas River. This market in its past is known as the Kapuas Indah Shopping Center, it experienced decreasing of quality or function shifting, along with the development of cities that grow the new economic areas that are more modern and millennial. At present, this market is still functioning but only limited to certain consumer market segments. Therefore, it is necessary to have repairing and developing in order to be able functioning optimally as the city public asset. In order to improve and redevelop the facilities in this market, the post-occupancy evaluation method needs for market physical facilities and infrastructure, this steps for developing physical facilities meet more targets in the future. This study uses qualitative exploratory methods with an investigative approach to analyze the aspect of behavior users of buildings and it functions of the Kapuas Indah Market and from these results of the analysis determined the problem handling strategies in it. The results of this study are strategies and recomendations for improving functional performance with regard to compatibility or suitability, namely the concept of statements about the quality of the relationship between user activities and the physical building of the Kapuas Indah Market. Second, adjustments related to human activities in the room, behavior related to equipment and possibilities of adaptation to the demands of building physics and the natural environment around the Kapuas Indah Market. Keywords: behavior; function; performance
The Top Health Care Stories of 2019: Cyberattacks and Hospital Data Security

Responses to a growing threat fall short.
A Dual-Task Interference Game-Based Experimental Framework for Comparing the Usability of Authentication Methods

This paper introduces a game-based framework to compare the usability of authentication methods. The framework uses a dual-task interference technique to determine the usability of authentication methods. In the experiment, subjects participate in a multi-tasking game that simulates a conversation being interrupted by authentication requirements. By simulating a conversation, the goal is to reproduce a real use of authentication, and collect ecologically sound data. Participants also perform each authentication method in a standalone manner, which allows for comparison of the usability under two different cognitive loads. The authentication techniques evaluated represent each of the three main authentication factors, specifically password, fingerprint, and coauthentication. The three aspects of usability used to compare authentication techniques in this framework are efficiency, effectiveness, and satisfaction. An experiment with 43 participants enrolled was conducted to collect data pertaining to these aspects. The results show that fingerprint and coauthentication (both laptop and phone) are the more usable techniques evaluated.
Recommendations for Tourism Sites Using the Mamdani Fuzzy Logic Method and Floyd Warshall Algorithm (Case Study in Yogyakarta)

Tourism is one of the activities carried out for recreation or leisure in a place with a variety of purposes and objectives. In Indonesia, many cities provide attractive tourism places, and one of them is the city of Yogyakarta. Because it has interesting and diverse tourism places, Yogyakarta is in great demand by local and foreign tourists. Thus to be able to maximize the visits of tourists who come to Yogyakarta, we need a system that is able to provide information on tourist attractions to tourists precisely in accordance with what the tourists want. The proposed system uses the Fuzzy Logic method and Floyd Warshall Algorithm which are combined, so as to obtain results in the form of recommendations for tourist attractions based on the costs of tourists, the length of time and distance needed to reach the tourist attractions.
Image Forgery: Restoration and Security

The problem of digital forgeries has become more and more serious in various fields like entertainment, digital forensics, and journalism. Due to the increasing amount of data in the world people uses public transfer medias like internet for storing and transferring data. Digital data can be transmitted  in a fast and inexpensive way through data communication networks without losing quality. So that most of us are use this way of communication. Malicious users or hackers can use this situation badly. Anyone with a clear knowledge in computer can alter the images by accessing from internet. The revised photo as a forensic evidence will distort the truth of the case badly. Tampered pictures on the social network can have a negative impact on the parties as well. In order to ensure the authenticity and integrity of digital media, there arise a need   of security techniques. In this paper, we are discussing about  the image restoration techniques from forgery and the security mechanisms to prevent images from further forgeries.
MxPool: Multiplex Pooling for Hierarchical Graph Representation Learning

How to utilize deep learning methods for graph classification tasks has attracted considerable research attention in the past few years. Regarding graph classification tasks, the graphs to be classified may have various graph sizes (i.e., different number of nodes and edges) and have various graph properties (e.g., average node degree, diameter, and clustering coefficient). The diverse property of graphs has imposed significant challenges on existing graph learning techniques since diverse graphs have different best-fit hyperparameters. It is difficult to learn graph features from a set of diverse graphs by a unified graph neural network. This motivates us to use a multiplex structure in a diverse way and utilize a priori properties of graphs to guide the learning. In this paper, we propose MxPool, which concurrently uses multiple graph convolution/pooling networks to build a hierarchical learning structure for graph representation learning tasks. Our experiments on numerous graph classification benchmarks show that our MxPool has superiority over other state-of-the-art graph representation learning methods.
Practical construction of positive maps which are not completely positive

This article introduces PnCP, a MATLAB toolbox for constructing positive maps which are not completely positive. We survey optimization and sum of squares relaxation techniques to find the most numerically efficient methods for this construction. We also show how this package can be applied to the problem of classifying entanglement in quantum states.
Aplikasi Artificial Neural Network (ANN) dalam Peramalan Time Series Data: Studi Kasus Lama Sinar Matahari

This research was conducted to study the Back Propagation ANN that was implemented with the Matlab GUI. Where the data used is the duration of shine data, the network architecture is formed by determining the number of units per layer. After the network is formed, training and testing are carried out from the data that has been grouped before. Furthermore, the prediction stage uses the trainer's training method with the log sig activation function of each layer. The number of input layer neurons is 120, the first hidden layer is 10, the second hidden layer is 10, the output layer is 1. While the maximum epoch parameter is 1000, the goal is 0.001, the learning rate is 0.7 and the step is 1. Based on the simulation results January was 51.25%, February was 62.00%, March was 59.29%, April was 64.52%, May was 71.42%, June was 79.32%, July was 64.25%, August was 77.87%, September was 85.02%, October was 81.33%, November of 56.67%, and December of 39.14%. The simulation results were obtained with MSE accuracy of 5.114, MAD of 1.479, MAPE of 2.162, RMSE of 2.261, and accuracy of 97.43%.
DEVELOPMENT OF FLOOD INUNDATION MAP USING RADAR IMAGES, CASE STUDY: LASOLO-KONAWEHA RIVER BASIN

The latest flood incident occurred  in the Lasolo-Konaweha River Basin in early June 2019. In solving the problem, initial assessment data is certainly needed, one of which is a flood inundation map. The method of generating flood inundation maps in Indonesia is currently generally constructed using local survey data, both using digital photos through drones and digital cameras that have many limitations in taking the mapped images, and generally in determining the inundation boundaries is only digitized by observer. So the flood inundation map has uncertainty and does not yet represent the actual conditions that occur in the flood area. In this study, flood inundation maps were generated using image data from Sentinel imagery and analyzed using the SNAP Desktop application. The method used in this application is to take the amplitude and intensity data from the Sentinel imagery before the flood to the flood conditions, then extract the spatial information based on the GLCM (Gray Level Co-Occurrence Matrix). The results of flood inundation maps produced from the analysis using the application are very smooth and almost close to the flood conditions that occur, so that development, both physical and non-physical carried out can precisely solve flooding problems that occur.
Gait Motion Analysis using Arduino and Blender 3d Software

The term 'Gait Analysis' refers to the scientific investigation of animal locomotion, particularly the human locomotion.Determination of gait functionalities, irregularities, and classifications are the main target of gait analysis so that better treatment is possible to provide for non ambulatory patients and also to provide gait enhancement facilities for military or disaster recovery applications.Gait analysis is used to assess and treat individuals with conditions affecting their ability to walk.This paper is intended to do the GAIT analysis of humans.GAIT analysis helps us to predict any problem related to our posture.In this project we will be using Arduino, arduino is an open-source hardware i.e singleboard microcontroller which will be placed on the joints present in the Human body e.g.neck, elbow, shoulder etc.To simulate the movements of the Human body we will do the animations in Blender Software which is completely free of cost and open source 3D computer graphics software toolset .The major focus of this project is to make a low-cost system as this project is intended for Indian citizens who are more conscious of the monetary issues.GAIT analysis using arduino and blender integration is a valid alternative to other expensive techniques.