Earticle

In order to reconstruct a 3D model in video sequences, to select key frames that are easy to estimate a geometric model is essential. This paper proposes a method to easily extract informative frames from a handheld video. The method combines selection criteria based on appropriate-baseline determination between frames, frame jumping for fast searching in the video, geometric robust information criterion (GRIC) scores for the frame-to-frame homography and fundamental matrix, and blurry-frame removal. Through experiments with videos taken in indoor space, the proposed method shows creating a more robust 3D point cloud than existing methods, even in the presence of motion blur and degenerate motions.

Among the methods of treating tinnitus, the transcutaneous clectrical nerve stimulation (TENS) method of treating by electrical stimulation is common. However, there is a problem that surgical operation is required to stimulate the vagus nerve (VN) main trunk near most of the bronchus. Alternatively, we found that the same effect could be achieved by electrically stimulating the vagus nerve VN branch (Arnold's nerve) distributed in the outer ear. The TENS system for stimulation of vagus nerve has been developed, but it has not been able to implement to stimulate as a parameter optimized for the patient by simultaneously playing the sound of eliminating the tinnitus frequency. Therefore, in this paper, it is important to develop a safe and practical TENS device for tinnitus treatment based on a 32-bit microprocessor that simultaneously applies non-invasive and notched sounds and to develop optimal treatment methods for treating tinnitus.

When a virtual sound source for 3D auditory system is reproduced by a linear loudspeaker array, listeners can perceive not only the direction of the source, but also its distance. Control over perceived distance has often been implemented via the adjustment of various acoustic parameters, such as loudness, spectrum change, and the direct-to-reverberant energy ratio; however, there is a neglected yet powerful cue to the distance of a nearby virtual sound source that can be manipulated for sources that are positioned away from the listener's median plane. This paper address the problem of generating binaural signals for moving sources in closed or in open environments. The proposed perceptual enhancement algorithm composed of three main parts is developed: propagation, reverberation and the effect of the head, torso and pinna. For propagation the effect of attenuation due to distance and molecular air-absorption is considered. Related to the interaction of sounds with the environment, especially in closed environments is reverberation. The effects of the head, torso and pinna on signals that arrive at the listener are also objectives of the consideration. The set of HRTF that have been used to simulate the virtual sound source environment for 3D auditory system. Special attention has been given to the modelling and interpolation of HRTFs for the generation of new transfer functions and definition of trajectories, definition of closed environment, etc. also be considered for their inclusion in the program to achieve realistic binaural renderings. The evaluation is implemented in MATLAB.

Recent development in multi-channel surround is emerging in various formats to provide better stereoscopic and sound effects to consumers in recent broadcasting. The ability sound localize the sound sources in space is most considerable design factor on multi-channel surround system for human earing perception model. However, this paper propose the change of the sound localization according to the spacing of the speakers, which is not covered in the existing research focus on sound system design. Presently the sound system uses the position and number of the speakers to localize the sound. In the multi-channel surround environment, the proposed design uses the sound localization is caused by the directional characteristics of the speaker, the distance between the speakers and the distance between the listener and the speaker according to the directivity is required. The proposed design is simulated using virtual measurement with MATLAB simulation environment and performances are measured.

In a cloud computing environment, a cryptographic service allows an information owner to encrypt the information and send it to a cloud server as well as to receive and decode encrypted data from the server which guarantees the confidentiality of shared information. However, if an attacker gains a coded data and has access to an encryption key via cloud server, then the server will be unable to prevent data leaks by a cloud service provider. In this paper, we proposed a key management server which does not allow an attacker to access to a coded key of the owners and prevents data leaks by a cloud service provider. A key management server provides a service where a server receives a coded public key of an information user from an owner and delivers a coded key to a user. Using a key management server proposed in this paper, we validated that the server can secure the confidentiality of an encryption key of data owners and efficiently distribute keys to data users

Machine learning is a field of artificial intelligence (AI), and a technology that collects, forecasts, and analyzes securities data is developed upon machine learning. The difference between using machine learning and not using machine learning is that machine learning—seems similar to big data—studies and collects data by itself which big data cannot do. Machine learning can be utilized, for example, to recognize a certain pattern of an object and find a criminal or a vehicle used in a crime. To achieve similar intelligent tasks, data must be more effectively collected than before. In this paper, we propose a method of effectively collecting data.

Journalism robot by using a computer algorithm, while maintaining the precision and reliability of the existing media refers to an article which is automatically created. In this paper, we introduce ‘stock robot' of robot journalism which writes securities articles and describe artificial intelligence algorithms in stages. Key steps of stock robot implemented artificial intelligence algorithm through four steps of data collection and storage, key event extraction, article content production, and article production. This research has developed a stock robot that collects and analyzes data on social issues and stock indexes for the last 2 years. In the future, as the algorithm is further developed, it becomes possible to write securities articles quickly and accurately through social issues. It will also provide customized information tailored to the user's preferences.

In this paper, all elements used in integrated infrastructure for job competency assessments of NCS (National Competency Standards) will be merged into assessment system using multiple devices(ASMD). NCS is a systematic approach on required abilities (knowledge, technical expertise, attitude) to process the tasks in the fields by industry. Competiveness of ASMD design is that no limitation of time and space using personal devices like PC, laptop, smartphone, and tablet, while seeing screen, hearing, touching, speaking, and writing. Question type can be limitless to express the situation. To lead technologies and market for domestic and oversea assessment system, supporting on multiple devices with connectivity that will eliminate limitation of time and space is the key feature for design competitiveness. Design of integrated assessment system proposed in this paper can be applied to NCS, fundamental competency evaluation, online test, job aptitude test, and foreign language test which involve listening, reading, writing, and speaking. Compared with existing evaluation method, reduction of investment and operating cost will be greater. Along with development of ICT technologies, the next generation of integrated assessment system will be quickly changed to ASMD, which already involves connected service between internet and smart devices.

Code-reuse attacks are very dangerous in various systems. This is because they do not inject malicious codes into target systems, but reuse the instruction sequences in executable files or libraries of target systems. Moreover, code-reuse attacks could be more harmful to IoT systems in the sense that it may not be easy to devise efficient and effective mechanism for code-reuse attack detection in resource-restricted IoT devices. In this paper, we propose a detection scheme with using Kullback-Leibler (KL) divergence to combat against code-reuse attacks in IoT. Specifically, we detect code-reuse attacks by calculating KL divergence between the probability distributions of the packets that generate from IoT devices and contain code region addresses in memory system and the probability distributions of the packets that come to IoT devices and contain code region addresses in memory system, checking if the computed KL divergence is abnormal.

This paper aims to improve the quality of cultural experience by providing a three - dimensional guide service that enables users to experience themselves without additional guides and cultural commentators using the latest mobile IT technology to enhance understanding of cultural heritage. In this paper, we propose a method of constructing cultural contents based on location information such as user / cultural heritage using markerless tracking based augmented reality and GPS. We use marker detection technology and markerless tracking technology to recognize smart augmented reality object accurately and accurate recognition according to the state of cultural heritage, and also use Android 's Google map to locate the user. The purpose of this paper is to produce content for introducing cultural heritage using GPS and augmented reality based on Android. It can be used in combination with various objects beyond the limitation of existing augmented reality contents.

When tooth grinding occurs, electrical stimulation is given at the same time, and tooth grinding stops on such stimulation. Electromyography signals are used as control signals of electrical stimulation to disturb tooth grinding. However because of the electrical stimulation, the M-waves are generated and mixed with spontaneous electromyogram. In this study, we designed an optimal filter to remove M-wave and conserve spontaneous electromyogram simultaneously. The inverse power method (IPM) showed that the optimal filter coefficient is the eigenvector corresponding to the minimum eigenvalue of the input covariance matrix. In order to evaluate the performance of the optimal filter, we compared using a conventional band pass filter and adaptive filter using least mean square algorithm. The experimental results show that the optimal filter can effectively remove the M-wave compared to the previously studied prediction error filter