13,010 research outputs found
Bongjun Kim
No full text학위논문(석사)--아주대학교 일반대학원 :산업공학과,2009. 8Abstract 1
Contents 2
I. Introduction 6
A. Research Motivation and Objective 6
B. Organization of Dissertation 10
II. Related Works 11
III. FlexRay Communication Cycle 14
IV. The System Architecture 17
V. Probabilistic Delay Analysis of Dynamic Message Transmission 22
A. Frame Delay Probability 22
B. Empty Minislot Distribution 23
VI. Performance Evaluation 26
A. Introduction 26
B. Frame Delay Probability 28
C. Empty Minislot Distribution and Frame Transmission Probability 33
VII. Conclustions 36
Bibliography 38MasterSince the safety and multimedia-related functions of automobile are getting increased and complex, In-vehicle network has become important. Even though FlexRay has emerged as the de-facto standard for In-vehicle network protocol, the message delay analysis problem has not been solved yet. In this thesis, we propose the probabilistic delay model of message transmission in the FlexRay dynamic segment considering the variable length of messages that share identical Frame Identifier (ID). Based on the model, we derive frame delay probability and empty minislot distribution as performance metrics, which can be used during the design phase of a FlexRay network, and also calculate transmission probabilities of additional message with new Frame ID for different lengths of it using the empty minislot probability. Finally, as model evaluation, we carry out simulation experiments with message sets that are randomly generated. Trough the experiments, we verify the models, and show that previous model only considering fixed frame length causes pessimistic delay probability compared to the proposed model. Empty minislot distribution and frame transmission probability is also analyzed for different value of system parameters of FlexRay. The delay model proposed is helpful for FlexRay system designer to determine system parameter or set frame information in DYN segment
Bongjun Kim
No full text학위논문(석사)--아주대학교 일반대학원 :경영학과,2007. 8지금까지 구전효과에 대한 수많은 연구가 진행되어 왔으며, 최근에는 이러한 관심이 온라인에서의 구전효과에 관한 연구로 이어져 오고 있다. 최근 온라인상에서는 디지털, 하이테크 제품을 중심으로, 해당 제품에 대한 전문성을 갖춘 전문 리뷰어가 제품을 평가하고, 그 결과를 자료와 함께 기사화하여 소비자에게 제품에 대한 비교/평가정보를 제공하는 리뷰 전문 웹사이트가 생겨나기 시작하였다. 이러한 리뷰 웹사이트에서 제공하는 리뷰기사의 평가정보는 효과적인 온라인 구전수단으로 작용할 수 있다.
따라서 본 연구에서는 온라인 구전에 관한 기존의 연구를 보다 확장하여, 기존 소비자들의 제품사용후기나 댓글에 비해 보다 제품에 대해 객관적이고 전문성을 갖춘 제품평가정보로서 제품 리뷰기사가 갖는 구전효과를 알아보고자 하였다. 연구1에서는 제품 리뷰기사가 구매의도에 미치는 효과와 리뷰기사 평가내용의 방향성의 효과를 알아보았다. 그 결과 제품 리뷰기사는 광고만 제공한 경우에 비해 구매의도에 영향을 미치는 것으로 나타났으며, 리뷰기사의 방향성에 따른 효과 또한 유의적이었다. 연구2에서는 리뷰기사의 평가정보, 제품에 대한 일반 소비자들의 댓글의견, 리뷰 전문 웹사이트의 신뢰도에 따라서 구매의도가 어떻게 달라지는지를 살펴보았다. 그 결과 리뷰기사와 댓글이 구매의도에 미치는 효과는 유의했으며, 리뷰기사의 효과는 웹사이트의 신뢰도 수준에 따라 조절되었다. 또한 리뷰기사와 댓글의견의 상호작용 효과도 나타났으며, 신뢰도에 따라 두 구전수단 사이의 상대적인 영향력이 달라짐을 확인하였다.
마지막으로 이러한 연구결과를 바탕으로 본 연구가 갖는 의미와 마케팅적 시사점을 도출하고, 연구의 한계 및 향후 연구의 방향에 대해 살펴보았다.제1장 서론
제1절 연구의 배경 및 필요성
제2절 연구의 목적
제2장 연구에 관한 이론적 고찰
제1절 구전 커뮤니케이션
1. 구전 커뮤니케이션의 개념 및 중요성
2. 온라인 구전 커뮤니케이션
3. 구전의 요인과 디지털 제품군에 대한 제품 평가정보
제2절 정보원의 신뢰도
1. 정보원의 신뢰도 개념과 중요성
2. 온라인에서의 웹사이트의 신뢰도
제3절 구매의도
제3장 연구1
제1절 연구가설 설정
제2절 연구설계
1. 연구대상 선정
2. 변수 설정 및 조작적 정의
3. 변수의 조작
4. 실험설계 및 절차
5. 측정
6. 분석방법
제3절 실험결과
1. 변수조작의 확인
2. 가설 검증 결과
제4장 연구2
제1절 연구가설 설정
제2절 연구설계
1. 연구대상 선정
2. 변수 설정 및 조작적 정의
3. 변수의 조작
4. 실험설계 및 절차
5. 측정
6. 분석방법
제3절 실험결과
1. 변수조작의 확인
2. 가설 검증 결과
제5장 결론
제1절 연구결과 요약 및 시사점
1. 연구결과 요약
2. 연구의 시사점
제2절 연구의 한계 및 향후 연구의 방향
[참고문헌]
[실험자극물]
[설문지]
[Abstract]Maste
Fine-grained Vocal Imitation Set
No full textThis dataset includes 763 vocal imitations of 108 sound events. The sound event recordings were taken from a subset of Vocal Imitation Set (zenodo.org/record/1340763). While the original VocalImitationSet only contains vocal imitations of a single reference recording per class, this new dataset contains vocal imitations of multiple reference recordings per class. Class names and filenames in this dataset are matched with the VocalImitationSet. Read the following paper to get more detailed information about VocalImitationSet.
[pdf] Bongjun Kim, Madhav Ghei, Bryan Pardo, and Zhiyao Duan, "Vocal Imitation Set: a dataset of vocally imitated sound events using the AudioSet ontology," *Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018)*, Nov. 2018.
Contact Info:
- Interactive Audio Lab: http://music.eecs.northwestern.edu
- Bongjun Kim [email protected] | http://www.bongjunkim.com
- Bryan Pardo [email protected] | http://www.bryanpardo.com</p
Vocal Imitation Set v1.1.3 : Thousands of vocal imitations of hundreds of sounds from the AudioSet ontology
No full text<p>The VocalImitationSet is a collection of crowd-sourced vocal imitations of a large set of diverse sounds collected from Freesound (<a href="https://freesound.org/">https://freesound.org/</a>), which were curated based on Google's AudioSet ontology (<a href="https://research.google.com/audioset/">https://research.google.com/audioset/</a>). We expect that this dataset will help research communities obtain a better understanding of human's vocal imitation and build a machine understand the imitations as humans do.</p>
<p>See <a href="https://github.com/interactiveaudiolab/VocalImitationSet">https://github.com/interactiveaudiolab/VocalImitationSet</a> for more information about this dataset and its latest updates.</p>
<p>For citations, please use this reference:</p>
<p>Bongjun Kim, Madhav Ghei, Bryan Pardo, and Zhiyao Duan, "Vocal Imitation Set: a dataset of vocally imitated sound events using the AudioSet ontology," <em>Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018)</em>, Nov. 2018.</p>
<p>Contact Info:</p>
<p>- Interactive Audio Lab: <a href="http://music.eecs.northwestern.edu/">http://music.eecs.northwestern.edu</a></p>
<p>- Bongjun Kim <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bongjunkim.com/">http://www.bongjunkim.com</a></p>
<p>- Bryan Pardo <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bryanpardo.com/">http://www.bryanpardo.com</a></p>
IAMHear
No full textIAMHear is a novel tabletop interface for music performance and sound making, in which smart mobile devices are used as on-table objects for interaction. Thanks to the advanced features of smart mobile devices, IAMHear is by nature multi-modal and highly interactive. The system also allows for acoustic location mechanism using virtually inaudible sound without any special sensors, making itself simpler in structure and easier to implement. In addition, use of”everyday objects“also evokes interaction by intuitive gestures such as placement, movement, and rotation. As a music sequencer, IAMHear enables the user to make music by placing objects on table; inspired by the idea of spectrographic mapping with virtual scan line, pitch and timbre of sounds are determined by the location/orientation of tabletop objects as well as ambient noise. We present IAMHear as a simple and novel alternative to interactive tabletop interface for music and various multimedia applications as well
Vocal Imitation Set v1.0 : Thousands of vocal imitations of hundreds of sounds from the AudioSet ontology
No full text<p>The VocalImitationSet is a collection of crowd-sourced vocal imitations of a large set of diverse sounds collected from Freesound (<a href="https://freesound.org/">https://freesound.org/</a>), which were curated based on Google's AudioSet ontology (<a href="https://research.google.com/audioset/">https://research.google.com/audioset/</a>). We expect that this dataset will help research communities obtain a better understanding of human's vocal imitation and build a machine understand the imitations as humans do.</p>
<p>See <a href="https://github.com/interactiveaudiolab/VocalImitationSet">https://github.com/interactiveaudiolab/VocalImitationSet</a> for the latest updates to this dataset.</p>
<p>Contact Info:</p>
<p>- Interactive Audio Lab: <a href="http://music.eecs.northwestern.edu/">http://music.eecs.northwestern.edu</a></p>
<p>- Bongjun Kim <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bongjunkim.com/">http://www.bongjunkim.com</a></p>
<p>- Bryan Pardo <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bryanpardo.com/">http://www.bryanpardo.com</a></p>
Integrated IoT Programming with Selective Abstraction
No full textThe explosion of networked devices has driven a new computing environment called the Internet of Things (IoT), enabling various services such as home automation and health monitoring. Despite the promising applicability of the IoT, developing an IoT service is challenging for programmers, because the programmers should integrate multiple programmable devices and heterogeneous third-party devices. Recent works have proposed integrated programming platforms, but they either require device-specific implementation for third-party devices without any device abstraction, or abstract all the devices to the standard interfaces requiring unnecessary abstraction of programmable devices. To integrate IoT devices with selective abstraction, this work revisits the object oriented programming (OOP) model, and proposes a new language extension and its compiler-runtime framework, called Esperanto. With three annotations that map each object to its corresponding IoT device, the Esperanto language allows programmers to integrate multiple programmable devices into one OOP program and to abstract similar third-party devices into their common ancestor classes. Given the annotations, the Esperanto compiler automatically partitions the integrated program into multiple sub-programs for each programmable IoT device, and inserts communication and synchronization code. Moreover, for the ancestor classes, the Esperanto runtime dynamically identifies connected third-party devices, and links their corresponding descendent objects. Compared to an existing approach on the integrated IoT programming, Esperanto requires 33.3% fewer lines of code to implement 5 IoT services, and reduces their response time by 44.8% on average.1
Rapid prototyping of IoT applications with Esperanto compiler
No full textIntegrating various networked devices, the Internet of Things (IoT) enables various new services like home automation, making its market larger and more competitive. Although rapid development of an IoT application is crucial to keep up with the highly competitive IoT market, developing an IoT application is challenging for programmers because the programmers should integrate multiple programmable devices and heterogeneous third-party devices. Some IoT frameworks integrate programming environments of multiple devices, but they either require device-specific implementation for third- party devices without any device abstraction, or abstract all the devices to the standard interfaces requiring unnecessary abstraction of programmable devices. This work introduces the Esperanto framework that integrates IoT devices with selective abstraction, allowing rapid prototyping of an IoT application. Exploiting the correspondence between an object and a thing in the object oriented programming (OOP) model, the Esperanto framework allows programmers to write only one OOP program instead of multiple programs for each device, and to manipulate third-party devices with their common ancestor classes. Compared to an existing approach on the integrated IoT programming, Esperanto requires 33.3% fewer lines of code to implement 5 IoT services, and reduces their response time by 44.8% on average. Moreover, with an empirical study, this work shows that the Esperanto framework reduces the development time by 52.7%.1
Precise Correlation Extraction for IoT Fault Detection With Concurrent Activities
No full textIn the Internet of Things (IoT) environment, detecting a faulty device is crucial to guarantee the reliable execution of IoT services. To detect a faulty device, existing schemes trace a series of events among IoT devices within a certain time window, extract correlations among them, and find a faulty device that violates the correlations. However, if a few users share the same IoT environment, since their concurrent activities make non-correlated devices react together in the same time window, the existing schemes fail to detect a faulty device without differentiating the concurrent activities. To correctly detect a faulty device in the multiple concurrent activities, this work proposes a new precise correlation extraction scheme, called PCoExtractor. Instead of using a time window, PCoExtractor continuously traces the events, removes unrelated device statuses that inconsistently react for the same activity, and constructs fine-grained correlations. Moreover, to increase the detection precision, this work newly defines a fine-grained correlation representation that reflects not only sensor values and functionalities of actuators but also their transitions and program states such as contexts. Compared to existing schemes, PCoExtractor detects and identifies 40.06% more faults for 4 IoT services with concurrent activities of 12 users while reducing 80.3% of detection and identification times.11Nsciescopu
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