• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.9-14
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• 2024

This study developed a voice recognition chatbot system to address depression and loneliness among the elderly in an aging society. The system utilizes the Whisper model, GPT 2.5, and XTTS2 to provide high-performance voice recognition, natural language processing, and text-to-speech conversion. Users can express their emotions and states and receive appropriate responses, with voice recognition functionality using familiar voices for comfort and reassurance. The UX/UI design considers the cognitive responses, visual impairments, and physical limitations of the smart senior generation, using high contrast colors and readable fonts for enhanced usability. This research is expected to improve the quality of life for the elderly through voice-based interfaces.

• The Journal of Information Systems
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• v.31 no.1
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• pp.239-269
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• 2022

Purpose This paper attempts to identify items for improving the usage of PLM(Product Lifecycle Management) systems and suggests ways to prioritize improvement items on the basis of importance. It also tries to find out differences in the importance of improvement items due to the company size, the industry, the job, or the PLM solution. Design/methodology/approach Through a survey from participants to a PLM System Conference, data were collected from a sample of 181 users who had the previous experience in using a PLM system. In order to figure out the differences in the importance among user groups, the F-test with the Scheffe test as a post-hoc analysis was used in case of equal variances and the Welch test with the Dunnett T3 test was used in case of unequal variances. Findings This study sorted out 25 improvement ideas according to their importance assessed by the PLM system users. The top five ideas are improving data consistency, error minimization, fast system response time, enhancing user recognition, and business process improvement. The support group puts higher importance than the general user group in data consistency, fast system response time, enhancing user recognition, business process improvement, dedicated team for data consistency, continuous support from management, hardware performance upgrade, output linkage to other systems, and shortening problem solving duration. The largest company group attaches significantly higher weights than the smallest company group to data consistency, error minimization, fast system response time, business process improvement, dedicated team for data consistency, security with proper access management, output linkage to other systems, and better user interface.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.112-121
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• 2008

Nowaday the supply chain competitiveness is emphasized more and more than a company's own competitiveness. One of the most important processes in import and export is a publication over the Bill of Loading. In the publication of those bills S/R(shipping request) and check B/L for reviewing are circulated among consignors, forwarders, shipping companies and airlines by fax and e-mail. Or there should be expensive a One to One system, like an EDI. Each party has to re-input S/R data to their own systems and check it several times. The S/R data are converted digital to analog type and analog to digital repeatedly to check in the process. As the process goes by there can be not only input data errors but also waste of time and cost. ECR(electronic character recognition) is a technology can solve the Problem. Considering the data structure of documents in many systems used ECR samples SIR data from documents written in the digital type. But it is not enough with it only. To make N to N composition in reality more efficient we make a documents hub on the web reengineering the existing process to One to One relation. The ECR documents hub system has given us beneficial effects over a year throughout a field test.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.1
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• pp.76-83
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• 2012

In a real-time indoor place recognition system using image features detection, specific markers included in input image should be detected exactly and quickly. However because the same markers in image are shown up differently depending to movement, direction and angle of camera, it is required a method to solve such problems. This paper proposes a technique to extract the features of object without regard to change of the object scale. To support real-time operation, it adopts SURF(Speeded up Robust Features) which enables fast feature detection. Another feature of this system is the user mark designation which makes possible for user to designate marks from input image for location detection in advance. Unlike to use hardware marks, the feature above has an advantage that the designated marks can be used without any manipulation to recognize location in input image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4903-4929
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• 2018

In this study, a fully automatic pose and expression invariant 3D face alignment algorithm is proposed to handle frontal and profile face images which is based on a two pass course to fine alignment strategy. The first pass of the algorithm coarsely aligns the face images to an intrinsic coordinate system (ICS) through a single 3D rotation and the second pass aligns them at fine level using a minimum nose tip-scanner distance (MNSD) approach. For facial recognition, multi-view faces are synthesized to exploit real 3D information and test the efficacy of the proposed system. Due to optimal separating hyper plane (OSH), Support Vector Machine (SVM) is employed in multi-view face verification (FV) task. In addition, a multi stage unified classifier based face identification (FI) algorithm is employed which combines results from seven base classifiers, two parallel face recognition algorithms and an exponential rank combiner, all in a hierarchical manner. The performance figures of the proposed methodology are corroborated by extensive experiments performed on four benchmark datasets: GavabDB, Bosphorus, UMB-DB and FRGC v2.0. Results show mark improvement in alignment accuracy and recognition rates. Moreover, a computational complexity analysis has been carried out for the proposed algorithm which reveals its superiority in terms of computational efficiency as well.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.1
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• pp.443-467
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• 2021

The purpose of this study was to conduct interviews with librarians who have experience in establishing local authority data by participating in the national authority sharing system of the National Library of Korea and to understand librarians' recognition and support for the joint utilization of national authority data. For this purpose, a total of 10 librarians who participated in the national authority sharing system project were interviewed by telephone using semi-structured questionnaires. Through this, it was possible to investigate the benefits, difficulties, utilization plans, revision plans of headings, and opinions on necessary support. The results of this study showed that the participants recognized that the joint utilization of national authority data provides the basis for the authority work of the local library and brings about the efficiency of the authority work, but they recognized the difficulty of modifying, selecting, creating new data, lacking knowledge, and lacking support system. The necessary support for the joint utilization of national authority data was provided with education and manuals related to authority, provision of rules related to authority that fully consider the position of the institution, budget and manpower support for system development and maintenance, establishment of communication channel and council, system and data advancement, and incentive to participating libraries. Based on the results of the study, the method and direction for the future operation of the joint utilization of national authority data were presented.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1180-1186
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• 2007

This paper contains that the current emergency response procedure through the railroad accident type at domestic and foreign, and the response program which is more systematic as a result of improving weaknesses. Because the response program at home is less sufficient than developed country's, we have made an investigation into system of classification in America, British, Germany, Japan for organizing separate emergency response code. we have researched the recognition response of five senses for minimizing the accident damage in a way of spreading the emergency response type analyzed through the accident procedure according to the feature of five senses by the first recognizer. Based on the first recognitions response of five senses, the scenario has been established according to each types and the criteria of accident has been researched through classifying the recognition of five senses response level, early response level, self-response level, outside support level.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.40-48
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• 2023

Speech Emotions recognition has become the active research theme in speech processing and in applications based on human-machine interaction. In this work, our system is a two-stage approach, namely feature extraction and classification engine. Firstly, two sets of feature are investigated which are: the first one is extracting only 13 Mel-frequency Cepstral Coefficient (MFCC) from emotional speech samples and the second one is applying features fusions between the three features: Zero Crossing Rate (ZCR), Teager Energy Operator (TEO), and Harmonic to Noise Rate (HNR) and MFCC features. Secondly, we use two types of classification techniques which are: the Support Vector Machines (SVM) and the k-Nearest Neighbor (k-NN) to show the performance between them. Besides that, we investigate the importance of the recent advances in machine learning including the deep kernel learning. A large set of experiments are conducted on Surrey Audio-Visual Expressed Emotion (SAVEE) dataset for seven emotions. The results of our experiments showed given good accuracy compared with the previous studies.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.11-12
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• 2016

SVM (Support Vector machine) is powerful machine-learning method, and obtains better performance than traditional methods in the applications of muti-dimension nonlinear pattern classification. For the case of SVM model training and low efficiency in large samples, this paper proposes a combination of statistical parameters of the GMM-UBM (Universal Background Model) model. It is very effective to solve the problem of the large sample for the SVM training. The experiment is carried on four special dynamic hand gestures using the EPIC sensors. And the results show that the improved dynamic hand gesture recognition system has a high recognition rate up to 96.75%.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.367-372
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• 2013

In Speech recognition system, there is a problem with phoneme in the model training and it cause a stored mode regeneration process which come into being appear time and more costs. In this paper, we propose the methode of likely phoneme model schema using decision tree clustering. Proposed system has a robust and correct sound model which system apply the decision tree clustering methode form generate model, therefore this system reduce the regeneration process and provide a retrieve the phoneme unit in probability model. Also, this proposed system provide a additional likely phoneme model and configured robust correct sound model. System performance as a result of represent vocabulary dependence recognition rate of 98.3%, vocabulary independence recognition rate of 98.4%.