The problem of underwater target detection and classification has been attracted a substantial amount of attention and studied from many researchers for both military and non-military purposes. The difficulty is complicate due to various environmental conditions. In this paper, we study classifier ensemble methods for active sonar target classification to improve the classification performance. In general, classifier ensemble method is useful for classifiers whose variances relatively large such as decision trees and neural networks. Bagging, Random selection samples, Random subspace and Rotation forest are selected as classifier ensemble methods. Using the four ensemble methods based on 31 neural network classifiers, the classification tests were carried out and performances were compared.

In video surveillance system, the exposure of a person's face is a serious threat to personal privacy. To protect the personal privacy in large amount of videos, an automatic face detection method is required to locate and mask the person's face. However, in real-world surveillance videos, the effectiveness of existing face detection methods could deteriorate due to large variations in facial appearance (e.g., facial pose, illumination etc.) or degraded face (e.g., occluded face, low-resolution face etc.). This paper proposes a new face detection method based on multi-level facial features. In a video frame, different kinds of spatial features are independently extracted, and analyzed, which could complement each other in the aforementioned challenges. Temporal domain analysis is also exploited to consolidate the proposed method. Experimental results show that, compared to competing methods, the proposed method is able to achieve very high recall rates while maintaining acceptable precision rates.

Nongroup Cellular Automata(CA) having two trees in the state transition diagram of a CA is suitable for pattern classifier which divides pattern set into two classes. Maji et al. [1] classified patterns by using multiple attractor cellular automata as a pattern classifier with dependency vector. In this paper we propose a method of generation of a pattern classifier using feature vector which is the extension of dependency vector. In addition, we propose methods for finding nonreachable states in the 0-tree of the state transition diagram of TPMACA corresponding to the given feature vector for the analysis of the state transition behavior of the generated pattern classifier.

Pedestrian detection (PD) is an essential task in various applications and sliding window-based methods utilizing HOG (Histogram of Oriented Gradients) or HOG-like descriptors have been shown to be very effective for accurate PD. However, due to exhaustive search across images, PD methods based on sliding window usually require heavy computational time. In this paper, we propose a real-time PD method for embedded visual surveillance with fixed backgrounds. The proposed PD method employs HOG descriptors as many PD methods does, but utilizes selective search so that it can save processing time significantly. The proposed selective search is guided by restricting searching to candidate regions extracted from Adaptive Gaussian Mixture Model (AGMM)-based background subtraction technique. Moreover, approximate computation of HOG descriptor and implementation in fixed-point arithmetic mode contributes to reduction of processing time further. Possible accuracy degradation due to approximate computation is compensated by applying an appropriate one among three offline trained SVM classifiers according to sizes of candidate regions. The experimental results show that the proposed PD method significantly improves processing speed without noticeable accuracy degradation compared to the original HOG-based PD and HOG with cascade SVM so that it is a suitable real-time PD implementation for embedded surveillance systems.

Recent research has been devoted and focused on detecting pedestrian and vehicle in intelligent vehicles except for the vulnerable road user(VRUS). In this paper suggest a new projection method which has robustness for rotation invariant and reducing dimensionality for each cell from original image to detect two-wheeler. We applied new weighting values which are calculated by maximum curvature containing very important object shape features and uniform local binary pattern to remove the noise. This paper considered the Adaboost algorithm to make a strong classification from weak classification. Experiment results show that the new approach gives higher detection accuracy than of the conventional method.

Current touch pen requires the special equipments to detect a touch and its price increases in proportion to the screen size. In this paper, we propose a method for detecting a touch and implementing a pen using the depth information. The proposed method obtains a background depth image using a depth camera and extracts an object by comparing a captured depth image with the background depth image. Also, we determine a touch if the depth value of the object is the same as the background and then provide the pen event. Using this method, we can implement a cheaper and more convenient touch pen.

In the Republic of Korea, there's been a culture called 'Hyo' since Koryo Dynasty and this word represents the meaning of paying utmost respects to one's own parents and ancestors whether they are alive or have passed. However, nowadays, most of people live away from their family gravesites so that they do not and cannot take care of them except on the special holidays. For this reason, people could not respond promptly to the incidents occurred at the sites as they receive notifications much later dates most of the time. Thus, in this paper, we propose a low-cost gravesite monitoring system which the users can immediately respond to the disastrous events after being informed of current situations through PLC without delay. For the performance evaluation, the lab and test bed experiments were performed on an actual ship using 200Mbps and 500Mbps products instead of performing an on-site experiment after the system has actually been constructed. The Mountain Region PLC was installed on the power lines and the result showed successful 36.14Mbps communication. Therefore, we expect that this study will contribute in time and cost reduction while constructing the internet infrastructures in mountain regions or building the Smart-graves, tumulus, and charnel houses.

This paper proposes a novel reversible secret sharing scheme using AES algorithm in encrypted images. In the proposed scheme, a role of the dealer is divided into an image provider and a data hider. The image provider encrypts the cover image with a shared secret key and sends it to the dealer. The dealer embeds the secret data into the encrypted image and transmits encrypted shadow images to the corresponding participants. We utilize Galois polynomial arithmetic operation over 2⁸ and the coefficient of the higher-order term is fixed to one in order to prevent the overflow. In experimental results, we demonstrate that the PSNR is sustained close to 44dB and the embedding capacity is 524,288 bits.

Due to rapid development of mobile device technologies, the mobile banking through Internet has become a major service of banking information systems as a security-critical information systems. Recently, lots of mobile banking information systems which handle personal and transaction information have been exposed to security threats in vulnerable security control and management processes, mainly software systems. Therefore, in this paper, we propose a process model for software security improvements in mobile banking information system by application of fault tree analysis(FTA) and failure modes and effects analysis(FMEA) on the most important activities such as 'user authentication' and 'access control' and 'virus detection and control' processes which security control and management of mobile banking information systems are very weak.

This paper proposes and implements a mobile service and web service integration for utilizing public bicycle sharing system NUBIJA. The NUBIJA system is operated by Changwon City, GyeongNam since 2008 and maintains 247 unattended bicycle sharing terminal on the city. Average users per day of the NUBIJA are more than 8,000 and many users want to get more services from their mobile phones. We implemented realtime mobile bicycle rental and return information service. The informations are acquired from each terminal kiosks and we integrated the information and location based services(LBS) on iOS and Android platform. In this paper, we described an integration services between web and mobile application and shows graphical user interface for highly customized on mobile platforms.

This paper proposes an automatic composition method using the training capability of artificial neural networks and chord progression rules that are widely used by human composers. After training a given song, the new melody is generated by the trained artificial neural networks through applying a different initial melody to the neural networks. The generated melody should be modified to fit the rhythm and chord progression rules for generating natural melody. In order to achieve this object, we devised a post-processing method such as chord candidate generation, chord progression, and melody correction. From some tests we could find that the melody after the post-processing was very improved from the melody generated by artificial neural networks. This enables our composition system to generate a melody which is similar to those generated by human composers.

In this paper, we propose a model which can prioritize the performance improvement work by analyzing the major risks and their influence, which can cause performance degradation in the system and show an example of a performance improvement using this model. In presentation-tier, as a result of log data analysis before and after the performance improvement of key processes which handle financial transactions, this model brought the CPU utilization and memory enhancement in the performance improvement work of the financial system which was carried out by applying the proposed model. It has been confirmed that the entire end-user can be accommodated. In the web-tier, the available memory increased by 200MB and we were able to improve the server restart(Recycling) that was sustained in the existing system. In the business logic-tier, we have been able to see better figures after performance improvements through the graph which analyzes the log collected with the key performance counters such as CPU%, Batch Requests/sec. In the data-tier, it has been confirmed that CPU usage and standby operation were reduced and the throughput was found to increase.

This paper aims to introduce the numerical methods for solving the optimal control theory to model bufferbloat problem. Mathematical tools are useful to provide insight for system engineers and users to understand better about what we are facing right now while experiment in a large-scale testbed can encourage us to implement in realistic scenario. In this paper, we introduce a survey of the numerical methods for solving the optimal control problem. We propose the dynamic optimization sweeping algorithm for optimal control of the active queue management. Simulation results in network simulator ns2 demonstrate that our proposed algorithm can obtain the stability faster than the others while still maintain a short queue length (≈10 packets) and low delay experience for arriving packets (0.4 seconds).

By according to the development of the mobile devices, a touch screen provides the variety of inputting character and the flexibility of user interface. Currently, the physically simple touch method is widely used for English input but this simple touch is not increasing the variety of inputs and flexibility of the user interfaces. In this paper, we propose a new method to input English characters continuously by recognizing gestures instead of the simple touches. The proposed method places the rotational pickers on the screen for changing the alphabetical sequence instead of the keys and inputs English characters through the flick gestures and the touches. Simulation results show that the proposed keypad method has better performance than the keypad of the conventional methods.

In recent times, studies sentiment analysis are being actively conducted by implementing natural language processing technologies for analyzing subjective data such as opinions and attitudes of users expressed on the Web, blogs, and social networking services (SNSs). Conventionally, to classify the sentiments in texts, most studies determine positive/negative/neutral sentiments by assigning polarity values for sentiment vocabulary using sentiment lexicons. However, in this study, sentiments are classified based on Thayer's model, which is psychologically defined, unlike the polarity classification used in opinion mining. In this paper, as a method for classifying the sentiments, sentiment categories are proposed by extracting sentiment keywords for major sentiments by using hashtags, which are essential elements of Instagram. By applying sentiment categories to user posts, sentiments can be determined through the similarity measurement between the sentiment adjective candidates and the sentiment keywords. The test results of the proposed method show that the average accuracy rate for all the sentiment categories was 90.7%, which indicates good performance. If a sentiment classification system with a large capacity is prepared using the proposed method, then it is expected that sentiment analysis in various fields will be possible, such as for determining social phenomena through SNS.

In the paper, we suggest bettered EHMECS(Enhanced Hybrid Multi Electrical Cupping System) to regulate automatically vacuum pressure using many cupping cup at once. We controlled accurately the pressure using S-PI control technique in pump motor to input the air inside cupping cup. S-PI control compared constant velocity, load and velocity variance between existing PI and FLC(Fuzzy Logic Control). The stabilization time of suggested S-PI control improve 20% of existing PI and 8% of FLC. The error constant of normal condition improved 71% of existing PI and 62% of FLC in steady speed and 80% of existing PI and 67% of FLC in load change. Also the error constant about velocity variance improve 45% of PI control. It is prove the suggested S-PI control technique. When use long time vacuum pressure of cupping cup regulated the suggested S-PI control technique, can loosen knotted muscles.

As the CEO`s of game companies should be ready for the rapid change of technical environment of game industry, highly skilled employees and the social capital become very important factors in doing game business. 2013 Korea Game White Paper shows that many game companies prefer employees with job experience. The social capital and network help game companies get industrial information easily. This study empirically examines the relationship among CEO`s related business experience, corporate performance and social capital based on 134 Korean game companies. CEO`s characteristics are measured by using demographic characteristics including age, amount of education, and prior job experience and psychological characteristics, but this study focuses on related business experience. The results of this study show some significant relationship between the related business experience of CEO and nonfinancial performance of the firm. Secondly, this study verifies the moderating effect of the social capital between the related business experience of CEO and non-financial performance of the firm. The results of the moderating effect of the social capital show that social capital increases the non-financial performance.

Distinguishing border between news and advertising is disappearing. Traditional journalism considered editorial part deals news and ad part handle commercial messages. But now this classification is meaningless. Current news consumers do not separate advertising content and non-advertising content. In Korea, making fake news or paid news pages is becoming social problem. Fake news uses various camouflages to pretend to be real news. This paper descriptively analyzed Korean fake news cases and suggested some guidelines for publishing news. We analyzed 3 major newspaper web sites from July to September, 2014. These three newspapers publish section pages everyday containing fake news or sponsored news. Totally more than one thousand articles were selected for content analysis. We coded the numbers of fake news, day of the week, the rate of sponsored news, average fake news publication number per pages, the conformity between news and advertising, and the type of fake news. We also coded the number of sponsored news article in day sections. We used method of comparing the advertising contents and news articles. As a result, 24.8% of news article were published for the advertising sponsors. Advertorial or fake news were sometimes arranged same pages the same day. We coded the conformity between same advertising and news content. More than 60 percent (60.9%) of fake news match with their sponsors. PR style of fake news is top and advertising type of fake news is the lowest.