Hybrid verrucous squamous cell carcinoma of sinonasal tract: a case report

Verrucous carcinoma is a variant of squamous cell carcinoma and should be distinguished from benign papilloma and well-differentiated nonverrucous squamous cell carcinoma. It is rare tumor of the sinonasal tract. Occasionally, conventional squamous cell carcinomatous components may be seen in verrucous carcinoma. This entity is called a hybrid verrucous squamous cell carcinoma. We report a case of hybrid verrucous squamous cell carcinoma occurring in the nasal cavity and paranasal sinus of a 67-year-old male. The removed mass shows the typical feature of verrucous carcinoma, but focally conventional squamous cell carcinomatous area is also noted. The treatment of this case follows verrucous carcinoma, but close follow up is mandatory because it may potentially spread to regional lymph nodes in contrast to pure form of verrucous carcinoma.     

Intelligent copyright protection system using a matching video retrieval algorithm

Many video service sites headed by YouTube know what content requires copyright protection. However, they lack a copyright protection system that automatically distinguishes whether uploaded videos contain legal or illegal content. Existing protection techniques use content-based retrieval methods that compare the features of video. However, if the video encoding has changed in resolution, bit-rate or codec, these techniques do not perform well. Thus, this paper proposes a novel video matching algorithm even if the type of encoding has changed. We also suggest an intelligent copyright protection system using the proposed algorithm. This can serve to automatically prevent the uploading of illegal content. The proposed method has represented the accuracy of 97% with searching algorithm in video-matching experiments and 98.62% with automation algorithm in copyright-protection experiments. Therefore, this system could form a core technology that identifies illegal content and automatically excludes access to illegal content by many video service sites.     

Laser glazing of an Fe-C-Sn alloy

Morphology and geometry of melted zones, cooling rates, microstructure and microhardness in the laser-glazed Fe-4%C-10%Sn alloy have been investigated. The computer simulation on the basis of the moving gaussian source model was used successfully to predict the maximum width and depth of the melted zone and the cooling rate. The microstructure from the surface to the bottom of the laser-melted zone is a non-crystalline phase, dendritic grains and a microcrystalline zone successively. Values of the averaged-spacing of the non-crystalline phase are 0.205⁶ and 0.121⁹nm, respectively; twinned martensites, having an axial ratioc/a of 1.128, existed in dendritic grains, and carbides of Fe₃ C at the interdendritic regions; the microcrystalline zone was composed of -Fe and a new bet (a=0.415 nm,c=0.955 nm) phase. The different microstructure in the melted zone can be explained by the results of the heat flow calculation. A fine eutectic structure (-Fe + Fe₃C) was observed in heat-affected zones. Microhardness of the eutectic structure can be predicted by the empirical relation of fracture stress to the interlamellar spacing of pearlite.     

Analysis of the correlation between acoustic noise and vibration generated by a multi-layer ceramic capacitor

Acoustic noise generated by a multi-layer ceramic capacitor (MLCC) makes users uncomfortable, so the problem must be analyzed to reduce the noise. There is a correlation between the acoustic noise and the vibration of MLCCs and the circuit board. Therefore, the acoustic noise problem must be investigated from a vibration perspective. In this study, the acoustic noise-generating mechanism was investigated, and the relationship between the characteristics of the noise and the dynamic characteristics of the circuit board with MLCC was analyzed. And a correlation criterion was proposed to predict the acoustic noise using the vibration response of the circuit board.     

Influence of continuous stabilization on the physical properties and microstructure of PAN-based carbon fibers

A continuous stabilization and carbonization process was used to prepare polyacrylonitrile (PAN)-based carbon fibers. The stepwise stabilization of PAN fibers was tried at various temperatures. The effect of stepwise stabilization on the physical properties and microstructure of the final carbon fibers is reported in this article. The fixed temperature in stepwise stabilization is kept below the fusion temperature of PAN precursors to avoid overstabilization of the fibers. The optimum stepwise stabilization process not only increases the amount of ladder polymer in stabilized fiber but also improves the physical and mechanical properties of the resultant carbon fibers. The formation of closed pores from open pores in carbon fiber occurs at 1100°C, but the formation of closed pores occurs at 200°C lower for carbon fiber developed from overstabilized fiber. The effect of continuous stepwise stabilization on the properties of resulting stabilized fibers and the variation in physical properties, element composition, and microstructure of carbon fibers during the carbonization process are also reported in this article.     

Pseudo-inversion: closure properties and decidability

We consider a pseudo-inversion operation inspired by biological events, such as DNA sequence transformations, where only parts of a string are reversed. We define the pseudo-inversion of a string \(w = uxv\) to be the set of all strings \(v^Rxu^R\), where \(uv \ne \lambda \) and consider the operation from a formal language theoretic viewpoint. We show that regular languages are closed under the pseudo-inversion operation whereas context-free languages are not. Furthermore, we study the iterated pseudo-inversion operation and show that the iterated pseudo-inversion of a context-free language is recognized by a nondeterministic reversal-bounded multicounter machine. Finally, we introduce the notion of pseudo-inversion-freeness and examine closure properties and decidability problems for regular and context-free languages. We demonstrate that pseudo-inversion-freeness is decidable in polynomial time for regular languages and undecidable for context-free languages.     

Usability Principles for Augmented Reality Applications in a Smartphone Environment

Through the rapid spread of smartphones, users have access to many types of applications similar to those on desktop computer systems. Smartphone applications using augmented reality (AR) technology make use of users' location information. As AR applications will require new evaluation methods, improved usability and user convenience should be developed. The purpose of the current study is to develop usability principles for the development and evaluation of smartphone applications using AR technology. We develop usability principles for smartphone AR applications by analyzing existing research about heuristic evaluation methods, design principles for AR systems, guidelines for handheld mobile device interfaces, and usability principles for the tangible user interface. We conducted a heuristic evaluation for three popularly used smartphone AR applications to identify usability problems. We suggested new design guidelines to solve the identified problems. Then, we developed an improved AR application prototype of an Android-based smartphone, which later was conducted a usability testing to validate the effects of usability principles.     

The determinants of continuous use of social networking sites: An empirical study on Taiwanese journal-type bloggers’ continuous self-disclosure behavior

The popularity and growth of social networking sites (SNSs) have resulted in fierce competition among SNS providers. A critical concern of SNSs is to identify how to have users continuously use a specific SNS. This study examines the determinants of journal-type bloggers’ continuous self-disclosure. An analysis of 283 samples with continuous self-disclosure experiences in journal-type blogs shows that personal factors, specifically the habit of self-disclosure, are the major factors affecting bloggers’ continuous self-disclosure, followed by self-benefits. In contrast, social factors, such as positive audience feedback and social benefits, are not related to continuous self-disclosure. These results suggest that SNS providers must encourage users to develop the habit of using their web sites regularly. By providing differential benefits to users, SNS providers may attract users to continuously use their services.     

Harmony search-based hidden Markov model optimization for online classification of single trial eegs during motor imagery tasks

This paper presents an improved method based on single trial EEG data for the online classification of motor imagery tasks for brain-computer interface (BCI) applications. The ultimate goal of this research is the development of a novel classification method that can be used to control an interactive robot agent platform via a BCI system. The proposed classification process is an adaptive learning method based on an optimization process of the hidden Markov model (HMM), which is, in turn, based on meta-heuristic algorithms. We utilize an optimized strategy for the HMM in the training phase of time-series EEG data during motor imagery-related mental tasks. However, this process raises important issues of model interpretation and complexity control. With these issues in mind, we explore the possibility of using a harmony search algorithm that is flexible and thus allows the elimination of tedious parameter assignment efforts to optimize the HMM parameter configuration. In this paper, we illustrate a sequential data analysis simulation, and we evaluate the optimized HMM. The performance results of the proposed BCI experiment show that the optimized HMM classifier is more capable of classifying EEG datasets than ordinary HMM during motor imagery tasks.     

A fast identification algorithm with outliers under Box-Cox transformation-based annealing robust radial basis function networks

In this article, a Box-Cox transformation-based annealing robust radial basis function networks (ARRBFNs) is proposed for an identification algorithm with outliers. Firstly, a fixed Box-Cox transformation-based ARRBFN model with support vector regression (SVR) is derived to determine the initial structure. Secondly, the results of the SVR are used as the initial structure in the fixed Box-Cox transformation-based ARRBFNs for the identification algorithm with outliers. At the same time, an annealing robust learning algorithm (ARLA) is used as the learning algorithm for the fixed Box-Cox transformation-based ARRBFNs, and applied to adjust the parameters and weights. Hence, the fixed Box-Cox transformation-based ARRBFNs with an ARLA have a fast convergence speed for an identification algorithm with outliers. Finally, the proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with Box-Cox transformation-based radial basis function networks.