• Smart Media Journal
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• v.13 no.1
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• pp.24-35
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• 2024

The combination of Artificial Intelligence and the Internet of Things (AIoT) has gained significant popularity. Deep neural networks (DNNs) have demonstrated remarkable success in various applications. However, deploying complex AI models on embedded boards can pose challenges due to computational limitations and model complexity. This paper presents an AIoT-based system for smart parking lots using edge devices. Our approach involves developing a detection model and a decision tree for occupancy status classification. Specifically, we utilize YOLOv5 for car license plate (LP) detection by verifying the position of the license plate within the parking space.

• ETRI Journal
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• v.38 no.5
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• pp.807-817
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• 2016

A novel fast algorithm is suggested for a coding unit (CU) mode decision using pseudo rate-distortion based on a separated encoding structure in High Efficiency Video Coding (HEVC). A conventional HEVC encoder requires a large computational time for a CU mode prediction because prediction and transformation procedures are applied to obtain a rate-distortion cost. Hence, for the practical application of HEVC encoding, it is necessary to significantly reduce the computational time of CU mode prediction. As described in this paper, under the proposed separated encoder structure, it is possible to decide the CU prediction mode without a full processing of the prediction and transformation to obtain a rate-distortion cost based on a suitable condition. Furthermore, to construct a suitable condition to improve the encoding speed, we employ a pseudo rate-distortion estimation based on a Hadamard transformation and a simple quantization. The experimental results show that the proposed method achieves a 38.68% reduction in the total encoding time with a similar coding performance to that of the HEVC reference model.

• ETRI Journal
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• v.36 no.4
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• pp.528-536
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• 2014

High Efficiency Video Coding (HEVC) is the most recent video coding standard to achieve a higher coding performance than the previous H.264/AVC. In order to accomplish this improved coding performance, HEVC adopted several advanced coding tools; however, these cause heavy computational complexity. Similar to previous video coding standards, motion estimation (ME) of HEVC requires the most computational complexity; this is because ME is conducted for three inter prediction modes - namely, uniprediction in list 0, uniprediction in list 1, and biprediction. In this paper, we propose an efficient inter prediction mode (EIPM) decision method to reduce the complexity of ME. The proposed EIPM method computes the priority of all inter prediction modes and performs ME only on a selected inter prediction mode. Experimental results show that the proposed method reduces computational complexity arising from ME by up to 51.76% and achieves near similar coding performance compared to HEVC test model version 10.1.

• Asia Marketing Journal
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• v.19 no.4
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• pp.15-36
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• 2018

Vietnamese luxury market is rapidly growing, however, there is a few researches on Vietnamese consumers' perceptions of luxury products and influential factors in purchasing intention. The purpose of this study is to explore Vietnamese consumers' value dimensions and mediating effect of social media information for their decision making for luxury product. Data were collected using self-administered mail survey. This study examines the influences of consumers' perceptions of quality and value, and social media word-of-mouth on Vietnamese consumers' luxury purchase intention.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.206-216
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• 2019

This study is focused on the factors which would influence new media's utilization based on the university students' survey and literacy adjustment effect. Through this process, we would verify the composition of new media's utilization and the importance of literacy ability which are needed for the survey of university students and try to find the effect factors for career decision making. We surveyed about 150 students who were studying in University located in Incheon city and analyzed the data of qualified 120 students. SPSS 23.0 was used and frequency analysis was performed to analyze the general characteristics of the students. Reliability analysis, correlation analysis and regression analysis were conducted to verify the contents of this study. The relationship, information and interest which were considered independent variables, were found to have a significant influence on the career decision making of the students. In addition, it was shown that the literacy adjustment effect also played a big role in career decision making of the students. Based on those findings, we discussed about the importance of contents in the utilization of new media, ways to improve the ability of literacy, the implications and limitations of this study.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.1
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• pp.27-32
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• 2016

In this paper, we proposed a soft decision-directed channel estimation based on MMSE estimation for MIMO-OFDM system. While the conventional method employs only pilot signals for channel estimation, the proposed algorithm performs channel estimation using pilot and reliable data signals. We also proposed selection criterion among reliable data signal for channel estimation. From numerical simulations, we show that the proposed channel estimator achieves 1 dB performance gain over conventional channel estimators.

• The Journal of Information Systems
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• v.24 no.1
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• pp.147-168
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• 2015

Why people reduce or stop using social network services(SNS), which are regarded as a mean of relationship and communication, unlike the early trend? To explain the phenomenon, this study tries to predict psychological decision making process of users from perspectives of cognitive dissonance theory. From this perspective, this study attempted an integrative approach that reflected 'User's literacy' indicating the ability of individuals to use SNS, and 'negative mass media influence' such as media reports on side effects or the bad experiences of acquaintances, along with the 3 factors used in the SNS Prior research. This study conducted an empirical analysis by surveying 256 facebook users, and the major findings are as follows:- First, Social-overload, complexity, uncertainty and negative media influence are significantly affect dissonance on the use of SNS. Second, Dissonance on the use of SNS significantly affects the behavior that possibly reduces and limits the use of SNS. In other words, the users who have experienced psychological dissonance respond passively by avoiding the use of SNS to resolve the dissonance. Third, the moderating effect of User's literacy wasn't a significant. This study presents a clue to understand psychological decision making process of use of SNS and a guideline for establishing practical strategies. In addition, it is important to note that this study contributes to expansion of theoretical discussion about usage.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.274-282
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• 2008

In this paper, we propose from media production environment using meta-data based on advanced authoring format(AAF). The media production system becomes digitalized since the image degradation and data storage should be minimized. For transmitting various contents without loss of meta-data. Editing decision list(EDL)is used in the current broadcasting and cinema environment, which results in inefficient performance. We compared the proposed AAF with the existing EDL cut, and tested successful transmission of the metadata. Based on the experimental results, the proposed AAF contains more video information than EDL.

• Smart Media Journal
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• v.2 no.2
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• pp.20-27
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• 2013

The concept of social media is top of the agenda for many business executives and decision makers, as well as consultants try to identify ways where companies can make profitable use of applications such as Netflix, Flixster. The social media is playing an increasingly important role as the information sources for customers making product choices etc. With the flourish of Web 2.0 technology, customer reviews are becoming more and more useful and important information resources for people to save their time and energy on purchasing products that they want. This paper proposes the Bayesian Probabilistic Classification algorithm to mine the social media review, and evaluates it by different splits and cross validation mechanism from the real data set. The explored study experimental results show the robustness and effectiveness of proposed approach for mining the social media review.

• Journal of Broadcast Engineering
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• v.20 no.6
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• pp.862-870
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• 2015

The RDO (Rate Distortion Optimization) process of HEVC results in good coding efficiency, but relatively requires much encoding time. In order to reduce the encoding time of RDO process, this paper proposes a method of fast intra prediction mode decision using DCT coefficients distributions and the existence of DCT coefficients. The proposed fast Intra coding sets the number of intra prediction mode candidates to three(3) from the RMD (Rough Mode Decision) process in HM16.0 reference SW and reduces the number of candidates one more time by investigating DCT coefficients distribution. After that, if there exists a quantized DCT block having all zero coefficient values for a specific candidate before the RDO process, the candidate is chosen without the RDO process. The proposed method reduces the encoder complexity on average 46%, while the coding efficiency is 2.1% decreased compared with the HEVC encoder.