• Management & Information Systems Review
• /
• v.9
• /
• pp.117-137
• /
• 2002

As attention to the Internet from both companies and individuals is rapidly on the increase, hundreds of new websites are opening in a single day. Along with such a high attention to the Internet, to set up an effective website needs efficient evaluation and reliable evaluation criterions for the website. The existing homepage contests and evaluation models are limited to certain websites in a special field or to the systemic side and to the contents, which in fact weakened the development of detailed evaluation sections and items possibly measured. This study is designed to integrate and seek out methods and success factors that should be considered when a website is built up, discovering evaluation criterions and making evaluation models objectively possible to be measured. The study focused on investigation into a new measurement standard and model by considering the previous studies, in order to suggest the followings: Centering the 7 top evaluation sections by type of each website such as (1) Service, (2) Mechanism, (3) Structure & Navigation, (4) Usability, (5) Contents (6) Community, (7) Communication, the study suggests an objective and reasonable website evaluation model on a basis of common factors considered in an integral and optimum view.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.7
• /
• pp.2377-2389
• /
• 2022

At present people have higher and higher requirements for network video quality, but video quality will be impaired by various factors, so video quality assessment has become more and more important. This paper focuses on the video quality assessment method using different fuzzy neural networks. Firstly, the main factors that impair the video quality are introduced, such as unit time jamming times, average pause time, blur degree and block effect. Secondly, two fuzzy neural network models are used to build the objective assessment method. By adjusting the network structure to optimize the assessment model, the objective assessment value of video quality is obtained. Meanwhile the advantages and disadvantages of the two models are analysed. Lastly, the proposed method is compared with many recent related assessment methods. This paper will give the experimental results and the detail of assessment process.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1590-1609
• /
• 2021

Laughter is one of the most important nonverbal sound that human generates. It is a means for expressing his emotions. The acoustic and contextual features of this specific sound are different from those of speech and many difficulties arise during their modeling process. During this work, we propose an audio laughter generation system based on unsupervised generative models: the autoencoder (AE) and its variants. This procedure is the association of three main sub-process, (1) the analysis which consist of extracting the log magnitude spectrogram from the laughter database, (2) the generative models training, (3) the synthesis stage which incorporate the involvement of an intermediate mechanism: the vocoder. To improve the synthesis quality, we suggest two hybrid models (LSTM-VAE, GRU-VAE and CNN-VAE) that combine the representation learning capacity of variational autoencoder (VAE) with the temporal modelling ability of a long short-term memory RNN (LSTM) and the CNN ability to learn invariant features. To figure out the performance of our proposed audio laughter generation process, objective evaluation (RMSE) and a perceptual audio quality test (listening test) were conducted. According to these evaluation metrics, we can show that the GRU-VAE outperforms the other VAE models.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.1
• /
• pp.180-194
• /
• 2021

For small image registration, feature-based approaches are likely to fail as feature detectors cannot detect enough feature points from low-resolution images. The classic FFT approach's prediction accuracy is high, but the registration time can be relatively long, about several seconds to register one image pair. To achieve real-time and high-precision rigid registration for small images, we apply deep neural networks for supervised rigid transformation prediction, which directly predicts the transformation parameters. We train deep registration models with rigidly transformed CIFAR-10 images and STL-10 images, and evaluate the generalization ability of deep registration models with transformed CIFAR-10 images, STL-10 images, and randomly generated images. Experimental results show that the deep registration models we propose can achieve comparable accuracy to the classic FFT approach for small CIFAR-10 images (32×32) and our LSTM registration model takes less than 1ms to register one pair of images. For moderate size STL-10 images (96×96), FFT significantly outperforms deep registration models in terms of accuracy but is also considerably slower. Our results suggest that deep registration models have competitive advantages over conventional approaches, at least for small images.

• Journal of Internet Computing and Services
• /
• v.24 no.5
• /
• pp.97-106
• /
• 2023

Citizens' demand for public CCTVs continues to rise, along with an increase in variouscrimes and social problems in cities. In line with the needs of citizens, the Seoul Metropolitan Government began installing CCTV cameras in 2010, and the number of new installations has increased by over 10% each year. As the large surveillance system represents a substantial budget item for the city, decision-making on location selection should be guided by reasonable standards. The purpose of this study is to improve the existing related models(such as public CCTV priority location analysis manuals) to establish the methodology foranalyzing priority regions ofSeoul-type public CCTVs and propose new mid- to long-term installation goals. Additionally, using the improved methodology, we determine the CCTV priority status of 25 autonomous districts across Seoul and calculate the goals. Through its results, this study suggests improvements to existing models by addressing their limitations, such as the sustainability of input data, the conversion of existing general-purpose models to urban models, and the expansion of basic local government-level models to metropolitan government levels. The results can also be applied to other metropolitan areas and are used by the Seoul Metropolitan Government in its CCTV operation policy

• Communications for Statistical Applications and Methods
• /
• v.19 no.3
• /
• pp.415-422
• /
• 2012

In this paper, we first the compare the performance of Holt-Winters, FSARIMA, AR-GARCH and Seasonal AR-GARCH models with in the short term based data. The results of the compared data show that the Holt-Winters model outperformed other models in terms of forecasting accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.4
• /
• pp.805-821
• /
• 2011

Wireless Sensor Networks (WSNs) are rapidly emerging because of their potential applications available in military and civilian environments. Due to unattended and hostile deployment environments, shared wireless links, and inherent resource constraints, providing high level security services is challenging in WSNs. In this paper, we revisit various security attack models and analyze them by using a well-known standard notation, Unified Modeling Language (UML). We provide a set of UML collaboration diagram and sequence diagrams of attack models witnessed in different network layers: physical, data/link, network, and transport. The proposed UML-based analysis not only can facilitate understanding of attack strategies, but can also provide a deep insight into designing/developing countermeasures in WSNs.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.8
• /
• pp.3473-3487
• /
• 2020

In this paper, we present a new approach to creating speech animation with emotional expressions using a small set of example models. To generate realistic facial animation, two example models called key visemes and expressions are used for lip-synchronization and facial expressions, respectively. The key visemes represent lip shapes of phonemes such as vowels and consonants while the key expressions represent basic emotions of a face. Our approach utilizes a text-to-speech (TTS) system to create a phonetic transcript for the speech animation. Based on a phonetic transcript, a sequence of speech animation is synthesized by interpolating the corresponding sequence of key visemes. Using an input parameter vector, the key expressions are blended by a method of scattered data interpolation. During the synthesizing process, an importance-based scheme is introduced to combine both lip-synchronization and facial expressions into one animation sequence in real time (over 120Hz). The proposed approach can be applied to diverse types of digital content and applications that use facial animation with high accuracy (over 90%) in speech recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.9
• /
• pp.4379-4397
• /
• 2017

Three different improvements of the Velocity-based model were proposed in a minimal velocity-based pedestrian model. The improvements of the models are based on the different agent forms. The different representations of the agent lead to different results, in this paper, we simulated the pedestrian movements in some typical scenes by using different agent forms, and the agent forms included the circles with different radiuses, the ellipse and the multi-circle stand for one pedestrian. We have proposed a novel model of pedestrian dynamics to optimize the simulation. Our model specifies the pedestrian behavior using a dynamic ellipse, which is parameterized by their velocity and can improve the simulaton accuracy. We found a representation of the pedestrian much closer to the reality. The phenomena of the self-organization can be observable in the improved models.

• Journal of the Korea Society for Simulation
• /
• v.8 no.1
• /
• pp.113-138
• /
• 1999

Driven by the explosive expansion and acceptance of the Internet and its multimedia front-end, the Web, a new generation of the modeling and simulation tools have come up with the name of Web-Based Simulation (WBS). Most of WBS libraries inherit its powerful advantages from Java. However, there are cases where explicit specification of models or interface objects is more desirable than the black-box programs. This paper presents an XML-based DEVS (Discrete Event System Specification) markup language for sharing simulation models on the Web. DEVS provides a system-theoretic formalism for the language while XML supports platform-independent data access. This paper focuses on the design of such a language.