• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.581-587
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• 2021

Real-time video streaming scheme for multimedia content delivery and remote conference services is one of technologies that are significantly sensitive to data transmission delay. Recently, because of COVID-19, real-time video streaming contents for the services are significantly increased such as personal broadcasting and remote school class. In order to support the services, there is a growing emphasis on low transmission delay and secure content delivery, respectively. Therefore, our research proposed a packet aggregation algorithm to reduce the transmission delay of selectively encrypted video transmission for real-time video streaming services. Through the application of the proposed algorithm, the selectively encrypted video framework can control the amount of MPEG-2 TS packets for low latency transmission with a consideration of packet priorities. Evaluation results on testbed show that the application of the proposed algorithm to the video framework can reduce approximately 11% of the transmission delay for high and low resolution video.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.4
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• pp.139-149
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• 2003

In this paper a hardware design of area-efficient hash processor which implements MD5 algorithm using hardware sharing and carry-save addition schemes is described. To reduce area, the processor adopts hardware sharing scheme in which 1 step operation is divided into 2 substeps and then each substep is executed using the same hardware. Also to increase clock frequency, three serial additions of substep operation are transformed into two carry-save additions and one carry propagation addition. The MD5 hash processor is designed using 0.25 $\mu\textrm{m}$CMOS technology and consists of about 13,000 gates. From timing simulation results, the designed MD5 hash processor has 465 Mbps hash rates for 512-bit input message data under 120 MHz operating frequency.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.89-96
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• 2022

This paper suggests heuristic algorithm for single-model cross-over assembly line balancing problem that is a kind of NP-hard problem. The assembly line balance problem is mainly applied with metaheuristic methods, and no algorithm has been proposed to find the exact solution of polynomial time, making it very difficult to apply in practice. The proposed bi-directional clustering algorithm computes the minimum number of worker m^* = ⌈W/c⌉ and goal cycle time c^* = ⌈W/m^*⌉ from the given total assembling time W and cycle time c. Then we assign each workstation i=1,2,…,m^* to T_i=c^* ±α≤ c using bi-directional clustering method. For 7 experimental data, this bi-directional clustering algorithm same performance as other methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.1-6
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• 2022

This paper deals with the maximum cardinality matching(MCM) problem. The augmenting path technique is well known in MCM. MCM is obtained by $O({\sqrt{n}}m)$ time complexity augmenting path algorithm for the general graph, and O(m log n) algorithm for the bipartite graph. On the other hand, this paper suggests O(n) linear time algorithm. The proposed algorithm based on the basic principle of as possible as largest selected inter-vertex edges in order to obtain the MCM. This paper simply selects edge {u,𝜐} that the minimum degree vertex u and minimum degree vertex 𝜐 in N_G(u) 𝜈(G)=k times iteration. For various general and bipartite graphs experimental data, this algorithm can be get the 𝜈(G) exactly.

• Journal of Distribution Science
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• v.20 no.5
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• pp.35-47
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• 2022

Purpose: To explain the effect of product quality, price perception, online distribution, and social media promotion on attitudes, customer satisfaction, and local brand love. Research design, data and methodology: The population of this study are Indonesians who have purchased local Indonesian brand products. The size of the sample used was 240 people with purposive sampling method. The analytical technique used is Path Analysis using SEM-PLS. Results: product quality, price perception, online distribution have a positive effect on attitudes, but social media promotion has a positive and insignificant effect on consumer attitudes; product quality, price perception, online distribution, and social media promotion have a positive and significant effect on customer satisfaction, and attitudes have a positive and significant effect on local brand love; and customer satisfaction has a positive effect on brand love for local brands. Conclusion: Therefore, it is important for local brand product businesses to pay attention to product quality, price perception, online distribution, and social media promotion in order to be able to build positive attitudes, customer satisfaction and ultimately have an impact on local brand love. In online distribution, with online distribution, it is easy for marketers to deliver multimedia content through online methods.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.203-212
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• 2022

In this paper, we propose to identify the factors and satisfaction of the selection of University and departments of One university freshmen. Research subjects were 499 freshmen in 2021 at K University located in G city. The data were analyzed by descriptive statistics, t-test, ANOVA, Scheffe' test and pearson's correlation coefficient using SPSS WIN 18.0. The results of this study showed that the internet/SNS was the highest in university information media, the school teacher was the highest in information provider, and the employment rate had the most impact on university registration decision. The University satisfaction score was 3.43, and there was a significant difference in gender(t=5.527, p=.019) and admission type(F=5.527, p<.001). The department satisfaction was 3.86 and there was a significant difference in the admissions type(F=3.004, p=.018). Univdrsity satisfaction and Department satisfaction showed a significant positive correlation(r=5.527, p<.001). Universities should improve their competitiveness through systematic admission information system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.95-101
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• 2022

The two-sided assembly line balancing problem is a kind of NP-hard problem. This problem primarily can be solved metaheuristic method. This paper suggests parallel clustering algorithm that each left and right-sided workstation assigned by operations with T_i = c^* ± α < c, c^* = ${\lceil}$W/m^*${\rceil}$ such that M^* = ${\lceil}$W/c${\rceil}$ for precedence diagram of two-sided assembly line with total complete time W and cycle time c. This clustering performs forward direction from left to right or reverse direction from right to left. For the 4 experimental data with 17 cycle times, the proposed algorithm can be obtain the minimum number of workstations m^* and can be reduce the cycle time to T_max < c then metaheuristic methods. Also, proposed clustering algorithm maximizes the line efficiency and minimizes the variance between workers operation times.

• KNOM Review
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• v.24 no.1
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• pp.20-28
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• 2021

Extensive use of social media applications and mobile devices continues to increase data traffic. Social media applications generate an endless and massive amount of multimedia traffic, specifically video traffic. Many social media platforms such as YouTube, Daily Motion, and Netflix generate endless video traffic. On these platforms, only a few popular videos are requested many times as compared to other videos. These popular videos should be cached in the user vicinity to meet continuous user demands. MEC has emerged as an essential paradigm for handling consistent user demand and caching videos in user proximity. The problem is to understand how user demand pattern varies with time. This paper analyzes three publicly available datasets, MovieLens 20M, MovieLens 100K, and The Movies Dataset, to find the user request pattern over time. We find hourly, daily, monthly, and yearly trends of all the datasets. Our resulted pattern could be used in other research while generating and analyzing the user request pattern in MEC-based video caching scenarios.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.175-182
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• 2022

In our daily life, we come across different types of information, for example in the format of multimedia and text. We all need different types of information for our common routines as watching/reading the news, listening to the radio, and watching different types of videos. However, sometimes we could run into problems when a certain type of information is required. For example, someone is listening to the radio and wants to listen to jazz, and unfortunately, all the radio channels play pop music mixed with advertisements. The listener gets stuck with pop music and gives up searching for jazz. So, the above example can be solved with an automatic audio classification system. Deep Learning (DL) models could make human life easy by using audio classifications, but it is expensive and difficult to deploy such models at edge devices like nano BLE sense raspberry pi, because these models require huge computational power like graphics processing unit (G.P.U), to solve the problem, we proposed DL model. In our proposed work, we had gone for a low complexity model for Audio Event Detection (AED), we extracted Mel-spectrograms of dimension 128×431×1 from audio signals and applied normalization. A total of 3 data augmentation methods were applied as follows: frequency masking, time masking, and mixup. In addition, we designed Convolutional Neural Network (CNN) with spatial dropout, batch normalization, and separable 2D inspired by VGGnet [1]. In addition, we reduced the model size by using model quantization of float16 to the trained model. Experiments were conducted on the updated dataset provided by the Detection and Classification of Acoustic Events and Scenes (DCASE) 2020 challenge. We confirm that our model achieved a val_loss of 0.33 and an accuracy of 90.34% within the 132.50KB model size.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.177-183
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• 2022

There is no known polynomial time algorithm for QAP that is a NP-complete problem. This paper suggests O(n²) polynomial time algorithm for random type quadratic assignment problem (QAP). The proposed algorithm suggests incremental augmenting matching strategy that is to set the matching set M={(l_i,f_j)} from l_i with minimum sum of distance in location matrix L and f_j with maximum sum of quantity in facility matrix F, and incremental augmenting of matching set M from M to l_i with minimum sum of distance and to f_j with maximum sum of quantity. Finally, this algorithm performs swap strategy that is to reflect the complex correlations of distances in locations and quantities in facilities. For the experimental data, this algorithm, in spite of O(n²) polynomial time algorithm, can be improve the solution than genetic algorithm a kind of metaheuristic method.