Earticle

본 연구는 만 19-25세의 남녀 대학생 성인을 대상으로 시청각 동영상 (audio-visual film clips)을 이용하여 여섯 가지 정서 -기쁨, 슬픔, 분노, 공포, 혐오, 놀람- 정서유발도구를 개발하고자 하였다. 이를 위하여 정서에 대한 심리반응을 평가하기 위한 정서평가척도도 개발하고자 하였다. 하나의 정서유발자극은 약 2분 30초-3분 30초 길이의 시청각 동영상으로 구성되어졌다. 실험참여자들은 각 정서장면을 시청한 후, 유발된 정서 상태에 대한 평가를 하였다. 예비실험을 통하여 총 열 개의 정서유발자극세트를 개발하였다. 각 세트에는 여섯 종류의 각각 다른 정서유발자극이 포함되어 있다. 정서의 적합성과 효과성을 분석한 결과, 정서유발자극은 80%이상을 나타내었다. 이는 개발된 정서유발자극들이 정서를 효과적으로 유발시키는 것으로 나타났다. “분노”와 “놀람” 정서자극들은 평균적으로 다른 정서자극들에 비하여 적합성과 효과성이 낮은 것으로 나타났다.

This study is to develop the emotion-inducing protocols using audio-visual film clips that produce six emotions, happiness, sadness, anger, fear, disgust, and surprise on college student, ranging 19-25 year old and standardize them. Additionally, emotion rating scales were also developed to measure psychological responses to each emotion. Each protocol consists of seven emotion pictures with about 2-3 minute long emotional scenes. All the subjects were to watch each emotional scene and were to evaluate emotions while they has watching them. A preliminary study was done to test the validity and ten protocols that produce emotions were developed. The results turned out that each protocol had over 80% of appropriateness and effectiveness, which implies these developed protocols are very effective in producing each basic emotion except anger and surprise.

In this paper, we propose a novel algorithm for watermarking in audio file with the advanced Wigner Distribution. In this approach, by decomposing the audio file into smaller frequency band using wavelet transform, the watermark message will be embedded in the most significant frequency band. The original file after broadcasting to the public will be changed by compression, quantization, etc. However, the main characteristic of the file does not change much. By employing this property, we embed the watermark message in the important frequency peaks of the original. The simulation results show that the algorithm is robust to strong attacks such as noise addition, filtering, and MP3 compression as well.

Early development of listening ability has been viewed as vital in the field of teaching English as a Foreign/Second Language (EFL/ESL). Both researchers and teachers have thus been greatly concerned with finding some ways to improve the learner’s listening competence, or better ideas to help learners acquire listening skills in the formal classroom setting. As one way of achieving this goal, this study spells out advantages of using technologically up-to-date audio/video data processing softwares over traditional audio/video players or CD/DVD players. These traditional language teaching aids have been of use and still can be to some extent. But they have been somewhat limited in terms of easier retrieval of necessary language input at the teacher’s will. For instance, when teachers try to use some specific parts of audio-video tapes for test construction, they have to spend a lot of time and energy cutting and pasting them. In addition, the audio/video quality often decreases in the process due to some technical problems. This study shows that both Digital Sound Processors (DSP) like Adobe Audition and Visual Data Processors (VDP) like Virtual Dub can be used so as to overcome those ever-existing limitations and thus to enhance ways of teaching listening. As a case study, this study comes up with a few practical ideas of how to apply language teaching materials made by using audio/video data processing programs to teaching listening, particularly for adult EFL learners.

The integration of deep learning techniques in the field of audio signal processing has marked a significant leap forward in the capability to analyze and classify complex sounds, including the nuanced and information-rich cries of infants. Deep learning's promise in this domain lies in its potential to decipher the subtle cues contained within these cries, offering insights into an infant's health, emotional state, and developmental needs. This potential application stands at the intersection of technology and healthcare, promising to enhance our understanding and response to the needs of the youngest members of society. This study experimentally demonstrates that a convolutional neural network–based audio classification model effectively learns discriminative spectral and temporal features from audio signals. Experimental results show that the proposed convolutional neural networks architecture achieves significantly higher classification accuracy than traditional machine-learning baselines, particularly when trained on spectrogram-based representations. The findings confirm that deep learning models not only improve overall performance but also provide robust generalization across different audio classes and noisy conditions.

This paper presents a robust audio retrieval method. In the method, the retrieval target is divided into short segments, each segment is searched respectively, and a retrieval window is used to maintain a list of segments that can be searched simultaneously. The method can quickly detect and locate known sound in real‐time audio stream, multimedia archives or the Internet. It can maintain high performance even if large part of target is absent in the input stream. Its retrieval speed can be adjusted by the length of retrieval window and is independent on target length. The recall rate and precision rate of the method are 100% and 99.7% respectively.

Anomaly recognition in visual and audio data has gained increasing significance in computer vision, as it plays a crucial role in protecting human lives and property. In this work, we developed a semi-supervised multimodal framework for anomaly recognition that combines audio and visual data for better performance. The proposed framework employs a hybrid network consisting of a convolutional neural network, Bi-Directional Long Short-Term Memory, a multi-head attention module, and a fully connected layer for anomalous pattern recognition. We created a novel real-time visual-audio anomaly recognition dataset and evaluated our framework on it, achieving promising results.

디지털 미디어 기술의 부단한 발전에 따라 뉴미디어 예술은 당대 예술 디자인 업계에 새로운 발전 기회를 가 져왔습니다.대학 캠퍼스 시청각 경관은 캠퍼스 경관 구성 시스템의 중요한 부분으로 캠퍼스 전체의 환경 쾌적 도를 높이고 환경 교육 효과를 촉진하는 등 대체 불가한 역할을 하고 있습니다.뉴미디어아트 속 다차원 디지 털 예술은 전통적인 예술 디자인 형태에 비해 색다른 미적 감각과 시각적 경험을 선사합니다.대학 캠퍼스 조 경 디자인은 대학 캠퍼스 전반의 외적인 환경 표현으로, 사제(師弟)의 대학 첫인상을 그대로 반영하고 있습니 다.현대 과학기술의 급속한 발전으로 뉴미디어아트의 표현 형식은 더욱 다채로워지고 새로운 표현방식이 끊임 없이 생겨나고 있습니다.본고에서는 뉴미디어아트의 응용탐구부터 시작하여 새로운 시대의 캠퍼스 영상음향 경관설계의 수요와 결합하여 뉴미디어아트의 캠퍼스 영상음향(Video and Audio) 경관설계에서의 혁신과 응용 을 탐구합니다.

With the continuous development of digital media technology, new media art has brought new development opportunities to the contemporary art and design industry. The audio-visual landscape of the university campus is an important part of the campus landscape composition system, which plays an irreplaceable role in improving the overall environmental comfort of the campus and promoting the educational effect of the environment. Compared with traditional forms of artistic design, multi-dimensional digital art in new media art has brought people different aesthetic and visual experiences. The landscape design of university campus is the external expression of the overall environment of university campus, which directly reflects the first impression of students and teachers on the University. Due to the rapid development of modern science and technology, the forms of expression of new media art have become more colorful, and new ways of expression have emerged. This paper starts with the exploration of the application of new media art, and discusses the innovation and application of new media art in the campus AV (Video and Audio) landscape design in combination with the needs of the new era of campus AV landscape design.

In this paper, a novel algorithm of audio watermarking is presented on the base of preattacking by predicting possible attacks for the special purpose of watermarking. Dividing frequency band in discrete wavelet transform (DWT) domain, and calculating the defined distortion measure, the appropriate band can be located to embed watermarking with hopping frequency technique. The imperceptible of audio host maintains by using psychoacoustics model to constrain the embedding strength. Experimental results show the proposed method obtains higher robustness to common watermarking attacks, especially for the forecasted attacks.

저작권(copyright)과 디지털 저작권 관리(Digital Right Management; DRM)에 대한 활발한 논쟁과 논의를 통해, 현재 디지털 콘텐츠에 대한 규제 및 제약들은 체계적으로 구축되고 있다. 그 결과, 디지털 오디오 플레이어와 같은 디지털 콘텐츠에 기반한 기기(device)의 시장은 향후 급속한 성장이 예상되며, 이러한 상황에서 디지털 오디오 플레이어와 관련된 시장 전략과 제품개발 전략의 개발이 요구되고 있다. 본 연구에서는 대표적인 디지털 오디오 기기인 MP3 플레이어를 중심으로 소비자의 수요에 영향을 미치는 요인들을 실증 분석을 통해 살펴보았다. 본 연구에서는 한국의 MP3 플레이어 시장에 대해 이산선택모형(discrete choice model)을 이용한 미시적(micro) 분석과 성장모형(growth model)을 이용한 거시적(macro) 분석을 실시하였으며, 이를 통해 MP3 플레이어 시장 전략과 함의를 도출하고 있다. 실증분석을 통해 본 연구에서는 매력적 품질요인(attractiveness requirement)들을 중심으로 한 마케팅 전략을 제시하였으며, 향후 연구방향을 제안하였다.

As a result of active discussion and debate concerning the copyright and digital rights management scheme, regulations and restrictions on digital content are well organized. Consequently, the market for the digital content oriented device, the digital audio player, is likely to grow further in scale. In this situation, the needs to develop market strategies and NPD strategies for the digital audio player are essential. This study investigates the factors that influence the consumer demand for MP3 player, which is a representative device of digital audio player, through empirical analysis. This study applies two analyses—�micro and macro market analysis, the first with the discrete choice model using panel survey data and the latter with the growth model—to the market of South Korea in order to establish market strategies and implications. The results of this study introduce an initiative marketing strategy as a suggestion for focusing on attractiveness requirements, along with possible future research directions.

In digital forensics, timestamps are crucial for analyzing key events in chronological order, making them vital to forensic investigations. This paper presents a method for detecting attempts to conceal a crime through the manipulation of timestamps on IT devices. Specifically, we introduce a technique to identify timestamp manipulation in a car’s infotainment system when the suspect's smartphone is connected via Bluetooth. The method involves extracting and analyzing Bluetooth Host Controller Interface (HCI) logs, Bluetooth logs, and system logs from both the smartphone and the infotainment system. Scenario-based experiments demonstrate the effectiveness of this technique in detecting timestamp manipulation on the infotainment system.