• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.2
• /
• pp.191-197
• /
• 2017

According to the ubiquitous usage of smartphone, so many smartphone applications have been developed, and especially data communications and position measurement technologies without additional equipments have been developed using acoustic signal. But there is a limitation to select the frequency of the acoustic signal due to the smartphone hardware, and there is non-linearity in the electronic circuits in a sound generation devices, the audible sound generated from the speaker is not avoidable. And it causes critical difficulty to the commercial system deployment. In this paper, a simulation technique to calculate the power of the audible acoustic signal by human is applied to several types of acoustic signals to evaluate the loudness. These could be referred when the acoustic communications or positioning systems are designed, for the purposed of inaudible sounding to human.

• The Journal of the Acoustical Society of Korea
• /
• v.42 no.3
• /
• pp.221-225
• /
• 2023

In this paper, we proposed an efficient method for rapid diagnosis of COVID-19 by voice. A novel Strided Convolution Separable Transformer (SC-SepTr) is proposed by modifying the conventional Separable Transformer (SepTr) for audio signal recognition. The proposed method reduces the memory and computational requirements to enable rapid diagnosis of COVID-19. As a result of experiments on Coswara, it was shown that the proposed method perform rapid diagnosis with guaranteeing Area Under the Curve (AUC) performance even for a relatively small amount of learning data.

• Journal of the Korea Convergence Society
• /
• v.9 no.4
• /
• pp.31-45
• /
• 2018

Recent dramatical development of computer technology related to internet technology intensifies the dispute over software of computer or smart device. Research on software has been flourished with political issuing of fierce competition among nations for software development. Particularly industrial growth in ethernet based big data and IoT (Internet of Things) has promoted to build and develop open source programs based on java, xcode and C. On these circumstances, issue on software piracy has been confronted despite the basic security policy protecting intellectual property rights of software and thus it is of substantial importance to protect the rights of originality of source program license. However, the other issue on source technology protection of developer is the possibility of hindrance to advancement in industry and culture by developing programs. This study discuss the way of enhancing legal stability of IoT application program development and reinforcing precision in inspection of program plagiarism by analyzing the source programs with newly introducing text mining technique, thus suggests an alternative protective way of infringement of personal information due to duplicating program.

• Journal of the Korean Society for information Management
• /
• v.24 no.2
• /
• pp.29-44
• /
• 2007

The purpose of this study was to explore whether the concept of amount of invested mental effort (AIME) developed in the field of educational psychology can help explain why people put so little effort into online searching. In this experimental study, two information retrieval systems - a web search engine and a university library system - were used to make a comparison. The data were collected from 15 undergraduate students through background questionnaires, think-aloud protocols, search logs, post-search questionnaires, and post-task interviews. The findings indicate that perception of the web's "easy-ness" and high levels of self confidence in searching capability led the subjects to put less effort into web searching than they do into library system searching. In addition, the perceived difficulty of search task influenced the extent of mental effort invested. The AIME proved a useful framework for understanding search behavior and user experience for both web search engines and library systems.

• Journal of Korea Multimedia Society
• /
• v.10 no.3
• /
• pp.391-400
• /
• 2007

According to the recent advances in multimedia computing, storage and searching technology have made large volume of music contents become prevalent. Also there has been increasing needs for the study on efficient categorization and searching technique for music contents management. In this paper, a new classifying method using the local information of music content and music tone feature is proposed. While the conventional classifying algorithms are based on entire information of music content, the algorithm proposed in this paper focuses on only the specific local information, which can drastically reduce the computing time without losing classifying accuracy. In order to improve the classifying accuracy, it uses a new classification feature based on music tone. The proposed method has been implemented as a part of MuSE (Music Search/Classification Engine) which was installed on various systems including commercial PDAs and PCs.

• The KIPS Transactions:PartD
• /
• v.13D no.5 s.108
• /
• pp.691-698
• /
• 2006

The companies need the enterprise-wide support environment to build the competency to gather VOM(Voice of Market) in the process of preparing and implementing the strategy and to help establishing and managing the business process in order to secure the continuous competitive edge The enterprise-wide support environment to establish, operate, improve and evaluate the business process must be carried out. In this paper we define the method to define process and business rule in order to enable accurate execution of the process. Furthermore, collection and refection of accurate data concerning the competency of individuals, the subjects of the process execution, allows prevention of weakness of the process execution result and is the basis for identifying the areas of improvement. Therefore, high visibility can be attained through the work knowledge and processes presented in rules, and it can help firmly establish the process centered work culture (or system) in the organization by process improvement strictly based on data.

• Journal of Platform Technology
• /
• v.9 no.3
• /
• pp.44-51
• /
• 2021

In general, golden time refers to the most important time in the initial response to accidents such as saving lives or extinguishing fires. The golden time varies from disaster to disaster, but is aimed at five minutes in terms of fire and first aid. However, for the actual site, the average dispatch time for ambulances is 9 minutes and the average transfer time is 17.6 minutes, which is quite large compared to the golden time. There are various causes for this delay, but the main cause is traffic jams. In order to solve the problem, the government has established emergency car concession obligations and secured golden time to prioritize ambulances in places with the highest accident rate, but it is not a solution in rush hour when traffic is increasing rapidly. Therefore, this paper proposed a deep learning-based emergency vehicle priority signal system using collected sound data by installing sound sensors on traffic lights and conducted an experiment to classify frequency signals that differ depending on the distance of the emergency vehicle.

• Journal of Korea Society of Industrial Information Systems
• /
• v.29 no.1
• /
• pp.91-105
• /
• 2024

Car accidents occur as a result of collisions between vehicles, leading to both vehicle damage and personal and material losses. This study developed a vehicle accident detection model based on 2,550 image frames extracted from car accident videos uploaded to YouTube, captured by CCTV. To preprocess the data, bounding boxes were annotated using roboflow.com, and the dataset was augmented by flipping images at various angles. The You Only Look Once version 8 (YOLOv8) model was employed for training, achieving an average accuracy of 0.954 in accident detection. The proposed model holds practical significance by facilitating prompt alarm transmission in emergency situations. Furthermore, it contributes to the research on developing an effective and efficient mechanism for vehicle accident detection, which can be utilized on devices like smartphones. Future research aims to refine the detection capabilities by integrating additional data including sound.

• Science of Emotion and Sensibility
• /
• v.15 no.4
• /
• pp.441-452
• /
• 2012

Recently, various researches have been attempted to effectively display pseudo-aural senses to the hearing-impaired or the deaf, using vibro-tactile stimulus as well as visual sense. Particularly, it is reported that as complementary senses to support the visual sense, tactile senses displayed by either speakers or vibration motors improve the reality sense significantly but do not nearly improve the emotional sense. Thus, in this study, the thermal sense is selected as another complementary sense to support the pseudo-aural sense display and it is investigated whether the thermal sense could generate a pseudo-aural sense or not. For this purpose, a thermal display module which could effectively display the desired thermal sense is implemented. Then, experiments have been conducted to subjects, which provide them with various types of stimuli combined with the aural, the vibrotactile, and the thermal stimuli along with the visual information. It can be confirmed, through statistical analysis on the data collected from experiments, that subjects could feel a pseudo-thermal sense closer to the real thermal sense which the normal subject feel from both the visual and the aural information, particularly either i) with the thermal stimulus along with the visual information or ii) with both the thermal and the vibrotactile stimuli along with the visual information than only with the visual information. Conclusively, it can be confirmed that the thermal stimulus applied to the skin of the subjects could play a role of effectively displaying pseudo-aural sense related to the thermal sense, as an complementary media for the pseudo-aural display.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.9
• /
• pp.95-104
• /
• 2009

This paper proposes the noise robust algorithm to detect the starting point of music. Detection of starting point of music is necessary to solve computational-waste problem and retrieval-comparison problem with inconsistent input data in music content based retrieval system. In particular, such detection is even more necessary in time sequential retrieval method that compares data in the sequential order of time in contents based music retrieval system. Whereas it has the long point that the retrieval is fast since it executes simple comparison in the order of time, time sequential retrieval method has the short point that data starting time to be compared should be the same. However, digitalized music cannot guarantee the equity of starting time by bit rate conversion. Therefore, this paper ensured that recognition rate shall not decrease even while executing high speed retrieval by applying time sequential retrieval method through detection of music starting point in the pre-processing stage of retrieval. Starting point detection used minimum wave model that can detect effective sound, and for strength against noise, the noises existing in mute sound were swapped. The proposed algorithm was confirmed to produce about 38% more excellent performance than the results to which starting point detection was not applied, and was verified for the strength against noise.