• Title/Summary/Keyword: quality features

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System Design and Application of External Feature Extraction for Quality Maintenance of Yukwa (유과의 품질규격 유지를 위한 외형 정보 측정 시스템 설계 및 적용 연구)

  • Cho, Sung Ho;Kim, Tae Jung;Hwang, Heon
    • The Korean Journal of Community Living Science
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    • v.24 no.2
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    • pp.251-258
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    • 2013
  • Korean oil and honey Yukwa has been paid attention as formal cake for traditional national seasons' holiday and religious service. Quality of Yukwa, however, has been maintained arbitrarily by each Yukwa manufacturer. Since even same Yukwa had severe differences in size, weight, and pattern, it has given the negative effect to the consumer. Yukwa industries need to setup the quantitative quality specifications instead of qualitative ones to maintain the uniformity of Yukwa quality. Efficient and economical inspection and process control system should be developed. In developing quality standards of Yukwa, features which can measure quality quantitatively in real time should be properly chosen. Existing quality features such as acidity, oxidization, hardness, viscosity, and texture were measured by the chemical or physical base destructive methods. Many research and developments have been performed in investigating and analyzing chemical transition states of those quality features as environment or storage condition changes. Most methods, however, require either off-line or complex treatment or time consuming process of analysis in evaluating quality features. Consumer, however, selects products mostly based on the external features such as shape, size, and color. Therefore, critical visual quality features should be chosen and the efficient real time measurement system must be developed. In this paper, computer image acquisition and processing system were developed and software modules were developed to extract the quantitative data of those features in real-time. Computer image processing system will promote in maintaining uniform quality of Yukwa and establishing quality standards of Yukwa.

Video Quality Assessment based on Deep Neural Network

  • Zhiming Shi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.8
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    • pp.2053-2067
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    • 2023
  • This paper proposes two video quality assessment methods based on deep neural network. (i)The first method uses the IQF-CNN (convolution neural network based on image quality features) to build image quality assessment method. The LIVE image database is used to test this method, the experiment show that it is effective. Therefore, this method is extended to the video quality assessment. At first every image frame of video is predicted, next the relationship between different image frames are analyzed by the hysteresis function and different window function to improve the accuracy of video quality assessment. (ii)The second method proposes a video quality assessment method based on convolution neural network (CNN) and gated circular unit network (GRU). First, the spatial features of video frames are extracted using CNN network, next the temporal features of the video frame using GRU network. Finally the extracted temporal and spatial features are analyzed by full connection layer of CNN network to obtain the video quality assessment score. All the above proposed methods are verified on the video databases, and compared with other methods.

Analysis of Voice Quality Features and Their Contribution to Emotion Recognition (음성감정인식에서 음색 특성 및 영향 분석)

  • Lee, Jung-In;Choi, Jeung-Yoon;Kang, Hong-Goo
    • Journal of Broadcast Engineering
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    • v.18 no.5
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    • pp.771-774
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    • 2013
  • This study investigates the relationship between voice quality measurements and emotional states, in addition to conventional prosodic and cepstral features. Open quotient, harmonics-to-noise ratio, spectral tilt, spectral sharpness, and band energy were analyzed as voice quality features, and prosodic features related to fundamental frequency and energy are also examined. ANOVA tests and Sequential Forward Selection are used to evaluate significance and verify performance. Classification experiments show that using the proposed features increases overall accuracy, and in particular, errors between happy and angry decrease. Results also show that adding voice quality features to conventional cepstral features leads to increase in performance.

Text-Confidence Feature Based Quality Evaluation Model for Knowledge Q&A Documents (텍스트 신뢰도 자질 기반 지식 질의응답 문서 품질 평가 모델)

  • Lee, Jung-Tae;Song, Young-In;Park, So-Young;Rim, Hae-Chang
    • Journal of KIISE:Software and Applications
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    • v.35 no.10
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    • pp.608-615
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    • 2008
  • In Knowledge Q&A services where information is created by unspecified users, document quality is an important factor of user satisfaction with search results. Previous work on quality prediction of Knowledge Q&A documents evaluate the quality of documents by using non-textual information, such as click counts and recommendation counts, and focus on enhancing retrieval performance by incorporating the quality measure into retrieval model. Although the non-textual information used in previous work was proven to be useful by experiments, data sparseness problem may occur when predicting the quality of newly created documents with such information. To solve data sparseness problem of non-textual features, this paper proposes new features for document quality prediction, namely text-confidence features, which indicate how trustworthy the content of a document is. The proposed features, extracted directly from the document content, are stable against data sparseness problem, compared to non-textual features that indirectly require participation of service users in order to be collected. Experiments conducted on real world Knowledge Q&A documents suggests that text-confidence features show performance comparable to the non-textual features. We believe the proposed features can be utilized as effective features for document quality prediction and improve the performance of Knowledge Q&A services in the future.

Wine Quality Classification with Multilayer Perceptron

  • Agrawal, Garima;Kang, Dae-Ki
    • International Journal of Internet, Broadcasting and Communication
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    • v.10 no.2
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    • pp.25-30
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    • 2018
  • This paper is about wine quality classification with multilayer perceptron using the deep neural network. Wine complexity is an issue when predicting the quality. And the deep neural network is considered when using complex dataset. Wine Producers always aim high to get the highest possible quality. They are working on how to achieve the best results with minimum cost and efforts. Deep learning is the possible solution for them. It can help them to understand the pattern and predictions. Although there have been past researchers, which shows how artificial neural network or data mining can be used with different techniques, in this paper, rather not focusing on various techniques, we evaluate how a deep learning model predicts for the quality using two different activation functions. It will help wine producers to decide, how to lead their business with deep learning. Prediction performance could change tremendously with different models and techniques used. There are many factors, which, impact the quality of the wine. Therefore, it is a good idea to use best features for prediction. However, it could also be a good idea to test this dataset without separating these features. It means we use all features so that the system can consider all the feature. In the experiment, due to the limited data set and limited features provided, it was not possible for a system to choose the effective features.

Categorizing Quality Features of Franchisees: In the case of Korean Food Service Industry (프랜차이즈 매장 품질요인의 속성분류: 국내 외식업을 중심으로)

  • Byun, Sook-Eun;Cho, Eun-Seong
    • Journal of Distribution Research
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    • v.16 no.1
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    • pp.95-115
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    • 2011
  • Food service is the major part of franchise business in Korea, accounting for 69.9% of the brands in the market. As the food service industry becomes mature, many franchisees have struggled to survive in the market. In general, consumers have higher levels of expectation toward service quality of franchised outlets compared that of (non-franchised) independent ones. They also tend to believe that franchisees deliver standardized service at the uniform food price, regardless of their locations. Such beliefs seem to be important reasons that consumers prefer franchised outlets to independent ones. Nevertheless, few studies examined the impact of qualify features of franchisees on customer satisfaction so far. To this end, this study examined the characteristics of various quality features of franchisees in the food service industry, regarding their relationship with customer satisfaction and dissatisfaction. The quality perception of heavy-users was also compared with that of light-users in order to find insights for developing differentiated marketing strategy for the two segments. Customer satisfaction has been understood as a one-dimensional construct while there are recent studies that insist two-dimensional nature of the construct. In this regard, Kano et al. (1984) suggested to categorize quality features of a product or service into five types, based on their relation to customer satisfaction and dissatisfaction: Must-be quality, Attractive quality, One-dimensional quality, Indifferent quality, and Reverse quality. According to the Kano model, customers are more dissatisfied when Must-be quality(M) are not fulfilled, but their satisfaction does not arise above neutral no matter how fully the quality fulfilled. In comparison, customers are more satisfied with a full provision of Attactive quality(A) but manage to accept its dysfunction. One-dimensional quality(O) results in satisfaction when fulfilled and dissatisfaction when not fulfilled. For Indifferent quality(I), its presence or absence influences neither customer satisfaction nor dissatisfaction. Lastly, Reverse quality(R) refers to the features whose high degree of achievement results in customer dissatisfaction rather than satisfaction. Meanwhile, the basic guidelines of the Kano model have a limitation in that the quality type of each feature is simply determined by calculating the mode statistics. In order to overcome such limitation, the relative importance of each feature on customer satisfaction (Better value; b) and dissatisfaction (Worse value; w) were calculated following the formulas below (Timko, 1993). The Better value indicates how much customer satisfaction is increased by providing the quality feature in question. In contrast, the Worse value indicates how much customer dissatisfaction is decreased by providing the quality feature. Better = (A + O)/(A+O+M+I) Worse = (O+M)/(A+O+M+I)(-1) An on-line survey was performed in order to understand the nature of quality features of franchisees in the food service industry by applying the Kano Model. A total of twenty quality features (refer to the Table 2) were identified as the result of literature review in franchise business and a pre-test with fifty college students in Seoul. The potential respondents of our main survey was limited to the customers who have visited more than two restaurants/stores of the same franchise brand. Survey invitation e-mails were sent out to the panels of a market research company and a total of 257 responses were used for analysis. Following the guidelines of Kano model, each of the twenty quality features was classified into one of the five types based on customers' responses to a set of questions: "(1) how do you feel if the following quality feature is fulfilled in the franchise restaurant that you visit," and "(2) how do you feel if the following quality feature is not fulfilled in the franchise restaurant that you visit." The analyses revealed that customers' dissatisfaction with franchisees is commonly associated with the poor level of cleanliness of the store (w=-0.872), kindness of the staffs(w=-0.890), conveniences such as parking lot and restroom(w=-0.669), and expertise of the staffs(w=-0.492). Such quality features were categorized as Must-be quality in this study. While standardization or uniformity across franchisees has been emphasized in franchise business, this study found that consumers are interested only in uniformity of price across franchisees(w=-0.608), but not interested in standardizations of menu items, interior designs, customer service procedures, and food tastes. Customers appeared to be more satisfied when the franchise brand has promotional events such as giveaways(b=0.767), good accessibility(b=0.699), customer loyalty programs(b=0.659), award winning history(b=0.641), and outlets in the overseas market(b=0.506). The results are summarized in a matrix form in Table 1. Better(b) and Worse(w) index indicate relative importance of each quality feature on customer satisfaction and dissatisfaction, respectively. Meanwhile, there were differences in perceiving the quality features between light users and heavy users of any specific franchise brand in the food service industry. Expertise of the staffs was labeled as Must-be quality for heavy users but Indifferent quality for light users. Light users seemed indifferent to overseas expansion of the brand and offering new menu items on a regular basis, while heavy users appeared to perceive them as Attractive quality. Such difference may come from their different levels of involvement when they eat out. The results are shown in Table 2. The findings of this study help practitioners understand the quality features they need to focus on to strengthen the competitive power in the food service market. Above all, removing the factors that cause customer dissatisfaction seems to be the most critical for franchisees. To retain loyal customers of the franchise brand, it is also recommended for franchisor to invest resources in the development of new menu items as well as training programs for the staffs. Lastly, if resources allow, promotional events, loyalty programs, overseas expansion, award-winning history can be considered as tools for attracting more customers to the business.

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Multimodal Fingerprint Matching Based on Minutiae Points and Directional Features (특징점 및 방향 특징에 기반한 멀티모달 지문 매칭)

  • Song, Young-Chul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.12
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    • pp.2529-2531
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    • 2009
  • A simple multimodal fingerprint recognition method based on two types of feature vectors such as minutiae points and directional features is proposed, where Directional Filter Bank (DFB) is used to extract directional features. Experimental results show that the proposed method can effectively combine minutiae- and DFB-based methods and produce a better matching capability in the poor quality fingerprint image.

No-Reference Image Quality Assessment based on Quality Awareness Feature and Multi-task Training

  • Lai, Lijing;Chu, Jun;Leng, Lu
    • Journal of Multimedia Information System
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    • v.9 no.2
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    • pp.75-86
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    • 2022
  • The existing image quality assessment (IQA) datasets have a small number of samples. Some methods based on transfer learning or data augmentation cannot make good use of image quality-related features. A No Reference (NR)-IQA method based on multi-task training and quality awareness is proposed. First, single or multiple distortion types and levels are imposed on the original image, and different strategies are used to augment different types of distortion datasets. With the idea of weak supervision, we use the Full Reference (FR)-IQA methods to obtain the pseudo-score label of the generated image. Then, we combine the classification information of the distortion type, level, and the information of the image quality score. The ResNet50 network is trained in the pre-train stage on the augmented dataset to obtain more quality-aware pre-training weights. Finally, the fine-tuning stage training is performed on the target IQA dataset using the quality-aware weights to predicate the final prediction score. Various experiments designed on the synthetic distortions and authentic distortions datasets (LIVE, CSIQ, TID2013, LIVEC, KonIQ-10K) prove that the proposed method can utilize the image quality-related features better than the method using only single-task training. The extracted quality-aware features improve the accuracy of the model.

Analysis of Consumer's Perception and Product Satisfaction·Dissatisfaction with Urban Outdoor Wear based on Kano Model: Focused on University Students (어반 아웃도어웨어에 대한 소비자 인식과 Kano 모델을 적용한 제품 만족·불만족에 대한 연구: 대학생을 중심으로)

  • Jun, Daegeun;Kim, Heekyoung;Kim, Hyeran;Park, Soonjee
    • Fashion & Textile Research Journal
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    • v.18 no.1
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    • pp.103-112
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    • 2016
  • This research was designed to figure out the perception and attitude of university students toward urban outdoor wear and to provide the guidelines for product quality improvement using Kano model. A total of 270 responses were analyzed by SPSS 20.0 through frequency and factor analysis. Respondents' levels for outdoor activity & outdoor products possession being still low, steady growth in urban outdoor wear market is expected. A total of eight quality factors were identified through factor analysis; suitability, production quality, functionality, ease of care, fabric performance, portability, fashionability, and symbolism. Based on Kano model, quality factors of urban outdoor wear were categorized into three groups: one-dimensional; indifferent; and must-be quality factor. It was found that consumers were satisfied with urban outdoor wear only when it meets the needs for suitability for body types and ease of care, meaning that manufactures should be cautious not to lose these features. Being must-be quality factor, production quality(form stability, quality of subsidiary materials), and fabric performance such as colorfastness should be basically satisfied. The relative importance of each quality feature on satisfaction/dissatisfaction was investigated using CSC(customer satisfaction coefficient). Based on the CSC, every item was classified again. Attractive quality features with large CSC were shown in suitability factor. Must-be quality features with small CSC were mainly shown in functionality and fabric performance factors. These findings imply that manufactures of urban outdoor wear should not only maintain the production quality but also focus on suitability features to differentiate their product with previous products.

A Study on the Effect of Accessible Design Features of Housing and Public Facilities on the Quality of Life of People with Disabilities (주택과 공공시설에서의 접근가능한 디자인 요소가 장애인의 삶의 질에 미치는 영향에 관한 연구)

  • Lee, So-Young;Yoo, Sung-Eun
    • Korean Institute of Interior Design Journal
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    • v.21 no.1
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    • pp.3-10
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    • 2012
  • There is a growing awareness that physical barriers affect the level of independence of people with disabilities. Many researchers insist that barrier free design could influence independence living and quality of life of the disabled. The purpose of this study is to find out the effects of accessible design features of house and public facilities on quality of life of disabled people. A total of 189 questionnaires from the disabled who visited public welfare facilities was analyzed. In order to find out what variables among accessible features in housing and public spaces impact quality of life, multiple regression analysis was carried using SPSS 14. The results showed that accessible designs significantly influence quality of life of the disable. The main reason in which the disabled have difficulties when they move outside is a lack of accessible amenities and facilities. Particularly in house design, accessible main entrance route and accessible main entrance door, and removal of floor level significantly affects quality of life of the disabled. For public spaces, accessible main entrance and installation of ramp or removal of floor levels of main entrance and corridor increase quality of life people with disabilities. This paper suggested that the improvement in housing and public space, in which regulation or bylaws do not specify, should be made to increase accessibility for life quality of the disabled.

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