Subjective Evaluation Measures Research Articles

Multi-hop Information-based Graph Convolutional Network for Clustering

Clustering is an essential and demanding undertaking in data analysis. The combination of traditional neural networks and graph convolutional networks (GCNs) has been extensively discussed in clustering tasks, in which the deep clustering methods learn useful content information and the graph convolutional networks mine the structured neighboring information in the graph data. However, the existing works equally consider the importance of different features to clustering and only focus on the nearest neighboring information in the structured features, ignoring the features of the long distant neighbors in the multi-hop information, resulting in inferior performance. We propose a novel multi-hop information-based graph convolutional network (MIGCN) for clustering to overcome these disadvantages. Specifically, we fuse content features and structured features with adaptive weights, which are dynamically adjusted according to the training results. Meanwhile, we utilize a multi-hop information module to extract structured features. Moreover, we design a multi-supervision mechanism and guide the training and updating of the whole model. Our method achieves better results than previous deep clustering approaches because it takes into account the diverse features embedded in the neural network and a dynamic fusion strategy for clustering. Our model has undergone rigorous testing on widely-accepted standard datasets, employing both objective and subjective evaluation measures. The results consistently demonstrate that our model consistently outperforms state-of-the-art techniques, validating its superior performance.

A Novel Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning.

Current deep learning (DL) based approaches to speech intelligibility enhancement in noisy environments are often trained to minimise the feature distance between noise-free speech and enhanced speech signals. Despite improving the speech quality, such approaches do not deliver required levels of speech intelligibility in everyday noisy environments. Intelligibility-oriented (I-O) loss functions have recently been developed to train DL approaches for robust speech enhancement. Here, we formulate, for the first time, a novel canonical correlation based I-O loss function to more effectively train DL algorithms. Specifically, we present a canonical-correlation based short-time objective intelligibility (CC-STOI) cost function to train a fully convolutional neural network (FCN) model. We carry out comparative simulation experiments to show that our CC-STOI based speech enhancement framework outperforms state-of-the-art DL models trained with conventional distance-based and STOI-based loss functions, using objective and subjective evaluation measures for case of both unseen speakers and noises. Ongoing future work is evaluating the proposed approach for design of robust hearing-assistive technology.

Subjective evaluation of floor impact noise using the tapping machine and a non-standardized source

Assessing the acoustical performance of building floor systems relies on the impact source to be utilized and on the type of floor cover used. Besides that, a reliable assessment should consider the listeners’ judgments of the sounds transmitted through floors or radiated by them. Objective ratings measured can help to foresee tenant satisfaction provided that they are well correlated with the listeners’ judgments. The main objective of this study was to compare objective and subjective evaluations, using two types of impact sources and two types of floor covers, to try and determine which objective variables could be used to predict subject evaluation and to validate the use of an alternative impact source to be used in more realistic measurements. An objective evaluation was carried out employing impact noise insulation measurements according to ISO 10140:2010, evaluating different types of floors, resilient materials, and impact sound sources (a standardized tapping machine and a calibrated tire). In the analysis of the measured samples, several parameters were evaluated according to the sound source used. Simultaneously, "sound samples" were recorded to be used in a subjective evaluation based on the judgments of 29 listeners about the Noise Annoyance and the Loudness Sensation in response to the two impact sources. The magnitude estimation method was used. Results demonstrate that tapping machine measurements correlate very well with the subjective evaluation measurements and the calibrated tire presents well-correlated results in a specific measurement set-up. In addition, linear regression analysis of the objective and subjective variables shows alternative single number quantities for ratings of impact noise insulation

Adaptive behavior and different thermal experiences of real people: A Bayesian neural network approach to thermal preference prediction and classification

Various observed and unquantifiable factors affect the thermal comfort of occupants in indoor environments and can lead to high uncertainty in the prediction and classification of their thermal preferences. The behavioral adaptation of occupants, by operating window systems for example, changes their thermal experience and expectations and therefore contributes to even higher prediction uncertainty. In this study, we applied a Bayesian neural network (BNN) algorithm to build a predictive model for occupant thermal preference using the ASHRAE Global Thermal Comfort Database II. The Bayesian method allows us to synthesize prior knowledge and available measurements into a unified modeling framework. It also offers a way to express and quantify uncertainty. Here we have performed a systematic study to test the efficiency and robustness of different BNN model configurations. The results show that the BNN model outperforms conventional thermal comfort models such as Predicted Mean Vote (PMV) and adaptive comfort model. The BNN model tends to produce more confident “prefer cooler” predictions with high possibility and low uncertainty. In contrast, the BNN model produces less certain predictions for “prefer no change” and “prefer warmer” across all occupants. Our findings suggest that linking occupants’ subjective evaluation measures and window opening/closing behavior to thermal comfort modeling effectively improves predictive performance.

Expression of Subjective Evaluation for the Participation Attitude to the Internet of Male College Students Based on Visual Analog Scale

This paper describes the expression of subjective evaluation for the participation attitude to the Internet of male college students using univariate scatter plot and box-and-whisker plot based on visual analog scale (VAS) by employing a small number of subjective evaluation measurement. 19 healthy male college students were invited as the experiment participants. In order to analyze their subjective evaluation for the participation attitude to the Internet, they were requested to answer the questionnaire on VAS (17 questions). The numerical results to show their subjective evaluation (applicable” or not applicable ) for the participation attitude to the Internet have been obtained, and they are shown by using the combination of univariate scatter plots and box-and-whisker plots. Moreover, it has been discovered that the question based on the similar subjective evaluation belongs to the same cluster. This fact is supported by the results of published article [12] analyzed in factor analysis. In addition, it has been also discovered that participants who have similar subjective evaluation values belong to the same cluster. The relationships and meanings for these questions or participants have been found by a small number of subjective evaluation measurement based on VAS.

An Efficient and Intelligent Recommender System for Mobile Platform

Recommender Systems are valuable tools to deal with the problem of overloaded information faced by most of the users in case of making purchase decision to buy any item. Recommender systems are used to provide recommendations in many domains such as movies, books, digital equipment’s, etc. The massive collection of available books online presents a great challenge for users to select the relevant books that meet their preferences. Users usually read few pages or contents to decide whether to buy a certain book or not. Recommender systems provide different value addition factors such as similar user ratings, users past history, user profiles, etc. to facilitate the users in terms of providing relevant recommendations according to their preferences. Recommender systems are broadly categorized into content based approach and collaborative filtering approach. Content based or collaborative filtering approaches alone are not sufficient to provide most accurate and relevant recommendations under diverse scenarios. Therefore, hybrid approaches are also designed by combining the features of both the content based and collaborative filtering approaches to provide more relevant recommendations. This paper proposes an efficient hybrid recommendation scheme for mobile platform that includes the traits of content based and collaborative filtering approaches in addition of the context based approach that is included to provide the latest books recommendations to user.Objective and subjective evaluation measures are used to compute the performance of the proposed system. Experimental results are promising and signify the effectiveness of our proposed hybrid scheme in terms of most relevant and latest books recommendations.

Voice conversion using General Regression Neural Network

The objective of voice conversion system is to formulate the mapping function which can transform the source speaker characteristics to that of the target speaker. In this paper, we propose the General Regression Neural Network (GRNN) based model for voice conversion. It is a single pass learning network that makes the training procedure fast and comparatively less time consuming. The proposed system uses the shape of the vocal tract, the shape of the glottal pulse (excitation signal) and long term prosodic features to carry out the voice conversion task. In this paper, the shape of the vocal tract and the shape of source excitation of a particular speaker are represented using Line Spectral Frequencies (LSFs) and Linear Prediction (LP) residual respectively. GRNN is used to obtain the mapping function between the source and target speakers. The direct transformation of the time domain residual using Artificial Neural Network (ANN) causes phase change and generates artifacts in consecutive frames. In order to alleviate it, wavelet packet decomposed coefficients are used to characterize the excitation of the speech signal. The long term prosodic parameters namely, pitch contour (intonation) and the energy profile of the test signal are also modified in relation to that of the target (desired) speaker using the baseline method. The relative performances of the proposed model are compared to voice conversion system based on the state of the art RBF and GMM models using objective and subjective evaluation measures. The evaluation measures show that the proposed GRNN based voice conversion system performs slightly better than the state of the art models.

The relationship between subjective outcome evaluation and objective outcome evaluation findings: evidence from China

AbstractThe relationships between subjective outcome evaluation and objective subjective evaluation measures were examined in this study. In a positive youth development program (Tin Ka Ping P.A.T.H.S. Project), 1083 high school students responded to objective outcome measures, including the Chinese Positive Youth Development Scale (CPYDS) and measures of thriving and life satisfaction at posttest. The respondents also responded to the Chinese Subjective Outcome Scale (CSOS) at posttest. Results showed that different measures derived from the CSOS (lessons, subject, sharing and benefits) had significant relationships with different measures of the CPYDS, thriving and life satisfaction. The different dimensions of the CSOS scores also predicted different objective outcome measures. The present findings provide additional evidence supporting the linkages between objective outcome and subjective outcome measures.

Analysis of errors in the automatic translation of questions for translingual QA systems

Purpose – This study aims to focus on the evaluation of systems for the automatic translation of questions destined to translingual question‐answer (QA) systems. The efficacy of online translators when performing as tools in QA systems is analysed using a collection of documents in the Spanish language.Design/methodology/approach – Automatic translation is evaluated in terms of the functionality of actual translations produced by three online translators (Google Translator, Promt Translator, and Worldlingo) by means of objective and subjective evaluation measures, and the typology of errors produced was identified. For this purpose, a comparative study of the quality of the translation of factual questions of the CLEF collection of queries was carried out, from German and French to Spanish.Findings – It was observed that the rates of error for the three systems evaluated here are greater in the translations pertaining to the language pair German‐Spanish. Promt was identified as the most reliable translato...

부산항 방파제 진입항로의 강한 횡조류 환경에서 선속에 따른 조종자의 선박조종의 결과 검토

이 논문은 부산항 방파제 진입항로에서 강한 횡조류가 있는 경우 60,000 DWT의 파나막스 선박의 조종에 있어 선속에 따른 영향을 파악하기 위하여 3년 이상의 선장 경력을 가진 76명의 조종자가 선박조종 시뮬레이션을 실시하고 그 결과를 선박의 근접도 계측, 제어도 계측, 조선자의 주관적 계측을 통하여 분석하기로 한다. 조류는 남서 방향, 2노트이고 독립 변수인 선속은 각각 5노트, 10노트로 한다. 시뮬레이션의 분석 결과는 다음과 같다. <TEX>${(1)}$</TEX> 부산항 방파제 진입항로에서 선속 5노트인 경우 드리프트 앵글을 <TEX>$10^{\circ}$</TEX> 이상으로 하는 것은 선수가 방파제 입구를 벗어나게 되므로 조종자는 심리적으로 이 각도 이상은 취하지 않는 경향이 있다. <TEX>${(2)}$</TEX> 선속 5노트에서의 경우가 선속 10노트보다 주관적 계측치, 선박의 근접도, 제어도가 상대적으로 크게 나타나고 있다. <TEX>${(3)}$</TEX> 선박의 제어도 계측 항목을 무차원화하여 이를 단일 지표로 표시하는 방법을 제안하였다. In order to ascertain the effect of ship's speeds, in maneuver under the condition of strong cross current in the breakwater channel of Busan port, this paper is to deal with the analyses of vessel proximity measures, vessel controllability measures, and ship handlers' subjective evaluation measures of simulated maneuvers, which were carried out by 76 ship handlers who conned Panamax bulk carrier of 60,000 DWT, The set and drift of current are southwesterly and 2 knots. The speeds of the model ship are 5 knots & 10 knots respectively. The followings are concluded. <TEX>${(1)}$</TEX> In the approaches of the breakwater of Busan port, ship handlers psychologically tend not to give the drift angle of more than <TEX>$10^{\circ}$</TEX> bemuse ship's head points out of the entrance. <TEX>${(2)}$</TEX> Ship handlers' subjective evaluation, vessel proximity and controllability measures are relatively larger under the speed of 5 knots than under that of 10 knots. due to direct pressure of strong current. <TEX>${(3)}$</TEX> A single index of controllability measures was suggested, by removing their units.

Clothing temperature changes of phase change material-treated warm-up in cold and warm environments

The purpose of this study was to investigate the appropriate amounts of phase change materials to give objective and subjective wear sensations. Vapor-permeable water-repellent fabrics with (WR-PCM) and without (WR) octadecane containing microcapsules were obtained by wet-porous coating process. Then, calculating the area of the WR-PCM treated clothes, we estimated the total calories of the clothing by multiplying the heat of fusion and heat of crystallization of PCM to the calculated area. Wear tests were conducted in both warm environment (30°C, 65 % RH) and cold environment (5°C, 65 % RH) with sports warm up style experimental garments made with WR and WR-PCM fabrics. Rectal, skin, and clothing microclimate temperatures, saliva and subjective evaluation measurements were done during the wear test. There was no difference of rectal and mean skin temperatures between WR and WR-PCM, but the clothing microclimate temperature of WR-PCM under warm environment was slightly lower than that of WR. In cold environment, WR-PCM showed much higher temperature than in WR. Saliva change did not appear between clothes, but did between two environments. Although subjective sensation between WR and WR-PCM was not significantly different, WR-PCM was rated as cooler than WR in warm environment and as warmer than WR in cold environment. The results of this study indicated that octadecane containing microcapsules in water-repellent fabric provide cooling effect.

A Preliminary Study of Sequencing Effects in Simulated Coach Feedback

In this study, experimenters (pseudo-coaches) provided feedback that varied in valence, sequence, and amount to 50 male college students. A laboratory analogue paradigm was used that included a basketball-like underhand free throw task in which subjects first were instructed on proper technique and then took 10 baseline shots (trials) followed by 2 blocks of 20 trials each. Subjects were randomly assigned. Some interacted with a pseudo-coach who made no comments during the two experimental trial blocks (control), while others received feedback (6-8 comments per trial block) that was response-specific, emotionally oriented, and provided in one of four sequences: positive-positive, negative-negative, positive-negative, or negative-positive. Based on prior research on coach behavior and social psychological studies of interpersonal behavior, we hypothesized that both of the continuous feedback groups would show performance decrements and associated reactions to the coach and the task. These predictions were supported regarding performance and, to some extent, regarding a measure of sustained self-observation. Discussion includes interpretation of the nominally superior performance of the control group, the nonsignificant results on the subjective evaluation measures, and implications of these findings in view of external validity criteria and prior analyses in the emerging behavioral technology of coaching.