Numerical stability of symmetric solitary-wave-like waves of a two-layer fluid—Forced modified KdV equation

Forced internal waves at the interface of a two-layer incompressible fluid in a two-dimensional domain with rigid horizontal boundaries are studied. The lower boundary is assumed to have a small obstruction. We derive a time-dependent forced modified KdV equation when the KdV theory fails and study the stabilities of four types of symmetric time-independent solitary-wave-like solutions numerically.     

I became an attractive person in the virtual world: Users’ identification with virtual communities and avatars

A number of studies have examined virtual worlds, which can facilitate knowledge sharing, education, and enjoyment, among others. However, no study has provided an insightful research model for evaluating virtual worlds. This study suggests that users’ identification with virtual communities and avatars plays a critical role in the construction of attractive virtual worlds. The proposed model measures the level of the user’s identification with virtual communities, through which the user builds his or her trust in other community members. In addition, the study suggests that users’ identification with avatars is an important element of their satisfaction with virtual worlds. The results indicate that users’ identification with virtual communities as well as avatars can enhance their efficacy and trust and thus facilitate their sustained use of virtual services. The results have important theoretical and practical implications.     

The role of self-construal in consumers’ electronic word of mouth (eWOM) in social networking sites: A social cognitive approach

The current study reconceptualized self-construal as a social cognitive indicator of self-observation that individuals employ for developing and maintaining social relationship with others. From the social cognitive perspective, this study investigated how consumers’ self-construal can affect consumers’ electronic word of mouth (eWOM) behavior through two cognitive factors (online community engagement self-efficacy and social outcome expectations) in the context of a social networking site. This study conducted an online experiment that directed 160 participants to visit a newly created online community. The results demonstrated that consumers’ relational view became salient when the consumers’ self-construal was primed to be interdependent rather than independent. Further, the results showed that such interdependent self-construal positively influenced consumers’ eWOM behavioral intentions through their community engagement self-efficacy and their social outcome expectations.     

Getting closer and experiencing together: Antecedents and consequences of psychological distance in social media-enhanced real-time streaming video

Social media services such as YouTube and Flickr have become online necessities for millions of users worldwide. Social media are online services that enable users to share contents, opinions, and perspectives that support communication with other users. Social media places an emphasis on the shared experience between users, which we call co-experience. However, the online characteristics of social media increase psychological distance between users, which, in turn, results in a decrease in the quality of co-experience. Hence, as the goal of this study, we theoretically modeled and empirically verified the antecedents and user experience-based consequences of psychological distance in a social media-enhanced real-time streaming video service. In order to reduce psychological distance, we introduced two system elements: inhabited space (the degree of being situated in context and in a meaningful place) and isomorph effects (the degree of preserving the structure of a user’s actions). We constructed a social media-enhanced real-time streaming video service prototype and conducted a field experiment with actual social media users. The prototype, which streamed a live baseball game, enabled users to simultaneously view the game from remote locations and to interact with each other through cheering tools. The results indicate that inhabited space and isomorph effects reduce psychological distance between users, and this, in turn, enhances co-experience. This paper ends with theoretical as well as practical implications of the study.     

Simultaneous optimization of artificial neural networks for financial forecasting

Artificial neural networks (ANNs) have been popularly applied for stock market prediction, since they offer superlative learning ability. However, they often result in inconsistent and unpredictable performance in the prediction of noisy financial data due to the problems of determining factors involved in design. Prior studies have suggested genetic algorithm (GA) to mitigate the problems, but most of them are designed to optimize only one or two architectural factors of ANN. With this background, the paper presents a global optimization approach of ANN to predict the stock price index. In this study, GA optimizes multiple architectural factors and feature transformations of ANN to relieve the limitations of the conventional backpropagation algorithm synergistically. Experiments show our proposed model outperforms conventional approaches in the prediction of the stock price index.     

Efficient scheme of verifying integrity of application binaries in embedded operating systems

Currently, embedded systems have been widely used for ubiquitous computing environments including digital setup boxes, mobile phones, and USN (Ubiquitous Sensor Networks). The significance of security has been growing as it must be necessarily embedded in all these systems. Up until now, many researchers have made efforts to verify the integrity of applied binaries downloaded in embedded systems. The research of problem solving is organized into hardware methods and software-like methods. In this research, the basic approach to solving problems from the software perspective was employed. From the software perspective, unlike in the existing papers (Seshadri et al., Proc. the IEEE symposium on security and privacy, 2004; Seshadri et al., Proc. the symposium on operating systems principals, 2005) based on the standardized model (TTAS.KO-11.0054. 2006) publicized in Korea, there is no extra verifier and conduct for the verification function in the target system. Contrary to the previous schemes (Jung et al. , 2008; Lee et al., LNCS, vol. 4808, pp. 346–355, 2007), verification results are stored in 1 validation check bit, instead of storing signature value for application binary files in the i-node structure for the purpose of reducing run-time execution overhead. Consequently, the proposed scheme is more efficient because it dramatically reduces overhead in storage space, and when it comes to computing, it performs one hash algorithm for initial execution and thereafter compares 1 validation check bit only, instead of signature and hash algorithms for every application binary. Furthermore, in cases where there are frequent changes in the i-node structure or file data depending on the scheme application, the scheme can provide far more effective verification performance compared to the previous schemes.     

Proactive Human Search for the Designated Person with Prior Context Information in an Undiscovered Environments

This paper describes a scheme for proactive human search for a designated person in an undiscovered indoor environment without human operation or intervention. In designing and developing human identification with prior information a new approach that is robust to illumination and distance variations in the indoor environment is proposed. In addition, a substantial exploration method with an octree structure, suitable for path planning in an office configuration, is employed. All these functionalities are integrated in a message- and component-based architecture for the efficient integration and control of the system. This approach is demonstrated by succeeding human search in the challenging robot mission of the 2009 Robot Grand Challenge Contest.     

Analysis of the false-positive error rate of tagged fragment marking scheme

IP traceback is an effective measure to deter internet attacks. A number of techniques have been suggested to realize IP traceback. The Fragment Marking Scheme (FMS) is one of the most promising techniques. However, it suffers a combinatorial explosion when computing the attacker?s location in the presence of multiple attack paths. The Tagged Fragment Marking Scheme (TFMS) has been suggested to suppress the combinatorial explosion by attaching a tag to each IP fragment. Tagging is effective because it allows the victim to differentiate IP fragments belonging to different routers, thereby greatly reducing the search space and finding the correct IP fragments. TFMS, however, increases the number of false positives when the number of routers on the attack path grows beyond some threshold. In this paper, we rigorously analyze the performance of TFMS to determine the correlation between the number of routers and the false positive error rate. Using a probabilistic argument, we determine the formulas for combination counts and error probabilities in terms of the number of routers. Under TFMS, our results show that we can reduce the required time to find an attacker?s location at the cost of a low error rate for a moderate number of routers.     

Subject-based extraction of a latent blog community

In the blogosphere, there exist posts relevant to a particular subject and blogs that show interest in the subject. In this paper, we define a set of such posts and blogs as a blog community and propose a method for extracting the blog community associated with a particular subject. The proposed method is based on the idea that the blogs who have performed actions (e.g., read, comment, trackback, scrap) to the posts of a particular subject are the ones with interest in the subject, and that the posts that have received actions from such blogs are the ones that contain the subject. The proposed method starts with a small number of manually-selected seed posts containing the subject. Then, the method selects the blogs that have performed actions to the seed posts over some threshold and the posts that have received actions over some threshold. Repeating these two steps gradually expands the blog community. This paper presents various techniques to improve the accuracy of the proposed method. The experimental results show that the proposed method exhibits a higher level of accuracy than the methods proposed in prior research. This paper also discusses business applications of the extracted community, such as target marketing, market monitoring, improving search results, finding power bloggers, and revitalization of the blogosphere.     

Video Panorama for 2D to 3D Conversion

Accurate depth estimation is a challenging, yet essential step in the conversion of a 2D image sequence to a 3D stereo sequence. We present a novel approach to construct a temporally coherent depth map for each image in a sequence. The quality of the estimated depth is high enough for the purpose of2D to 3D stereo conversion. Our approach first combines the video sequence into a panoramic image. A user can scribble on this single panoramic image to specify depth information. The depth is then propagated to the remainder of the panoramic image. This depth map is then remapped to the original sequence and used as the initial guess for each individual depth map in the sequence. Our approach greatly simplifies the required user interaction during the assignment of the depth and allows for relatively free camera movement during the generation of a panoramic image. We demonstrate the effectiveness of our method by showing stereo converted sequences with various camera motions.