In this paper, we propose a method of measuring bone mineral density in a peripheral-type clinical X-ray CT using a phantom, and we propose a method of classifying osteoporosis using bone mineral density and bone structure parameters together. It segments the trabecular bone region and cortical bone region for the six sections of the phantom and calculates the average HU value of the segmented regions. By using these values, it derives an expression converting HU value to bone mineral density. It segments trabecular bone of 1 cm region in the end part of distal radius and extracts the bone mineral density and structural parameters for the trabecular bone region. We extracted bone mineral density and structural parameters for the 18 subjects each of normal and osteoporotic group. We carried out classification experiments using three classification methods; SAD, SVM, ANN. The sensitivity, specificity, accuracy, positive predictive value, negative predictive value, likelihood ratio of the classification was improved in the order of ANN, SVM and SAD. Also, The sensitivity, specificity, accuracy, positive predictive value, negative predictive value, likelihood ratio of the classification was improved when we use the bone mineral density and structural parameters together.

Images taken from outdoor are degraded quality by fog or haze, etc. In this paper, we propose a method that provides the visibility improved images through fog or haze removal. We proposed haze removal method that uses brightness transform based on atmospheric scatter coefficient rate with local histogram equalization. To calculate the transmission rate that indicate fog rate in original image, we use atmospheric scatter coefficient rate based on quadratic equations about haze model. And primary brightness transformed image can be obtained by using the obtained transmission rate. Also we use local histogram equalization with proposed brightness transform for effectively image visibility enhancement. Unlike existing methods, our method can process real-time with stable and effect image visibility enhancement. Proposed method use only the luminance images processed by good performance surveillance systems because it represents the real-time processing is required, black-box, digital camera and multimedia equipment is applicable. Also because it shows good performance only with the luminance images processed, Surveillance systems, black boxes, digital cameras, and multimedia devices etc, that require real-time processing can be applied.

Hidden Markov Model is one of the most successful and popular tools for modeling real world sequential data. Real world signals come in a variety of shapes and variabilities, among which temporal and spectral ones are the prime targets that the HMM aims at. A new problem that is gaining increasing attention is characterizing missing observations in incomplete data sequences. They are incomplete in that there are holes or omitted measurements. The standard HMM algorithms have been developed for complete data with a measurements at each regular point in time. This paper presents a modified algorithm for a discrete HMM that allows substantial amount of omissions in the input sequence. Basically it is a variant of Baum-Welch which explicitly considers the case of isolated or a number of omissions in succession. The algorithm has been tested on online handwriting samples expressed in direction codes. An extensive set of experiments show that the HMM so modeled are highly flexible showing a consistent and robust performance regardless of the amount of omissions.

Recently, the competition among global IT companies for the market occupancy of the IoT(Internet of Things) is fierce. Internet of Things are all the things and people around the world connected to the Internet, and it is becoming more and more intelligent. In addition, for the purpose of providing users with a customized services to variety of context-awareness, IoT platform and related research have been active area. In this paper, we analyze third party instant messengers of Windows 8 Style UI and propose a digital forensic methodology. And, we are well aware of the Android-based map and navigation applications. What we want to show is GPS information analysis by using the R. In addition, we propose a structured data analysis applying the hierarchical clustering model using GPS data in the digital forensics modules. The proposed model is expected to help support the IOT services and efficient criminal investigation process.

Moblie device based financial services are vulnerable to social engineering attacks because of the display screen of mobile devices. In other words, in the case of shoulder surfing, attackers can easily look over a user's shoulder and expose his/her password. To resolve this problem, a colour-based secure keyboard solution has been proposed. However, it is inconvenient for genuine users to verify their password using this method. Furthermore, password colours can be exposed because of fixed keyboard colours. Therefore, we propose a secure mobile authentication method to provide advanced functionality and strong privacy. Our authentication method is robust to social engineering attacks, especially keylogger and shoulder surfing attacks. According to the evaluation results, our method offers increased security and improved usability compared with existing methods.

Physical security protecting people from physical threats, such as a person or vehicle, has received a great attention. However, it has many risks of hacking and other security threats because it is highly dependent on automated management systems. In addition, a representative system of physical security, a CCTV control system has a high risk of hacking, such as video interceptions or video modulation. So physical security needs urgent security measures in accordance with these threats. In this paper, we examine the case of security threats that have occurred in the past, prevent those from threatening the physical security, and analyze the security problem with the threats. Then we study the countermeasures to prevent these security threats based on the problems found in each case. Finally we study for the method to apply these countermeasures.

PC users have long been controlling their computers using input devices such as mouse and keyboard. To improve inconveniences of these devices, the method of screen-touching has widely been used these days, and devices recognizing human gestures are being developed one after another. Fox example, Kinect, developed and distributed by Microsoft, is a non-contact input device that recognizes human gestures through motion-recognizing sensors, thus replacing the mouse as an input device. However, when controlling the mouse on a large screen, it suffers from the problem of requiring large motions in order to move the mouse pointer to the edges of the screen. In this paper, we propose a joystick-driven mouse-controlling method which enables the user to move the mouse pointer to the corners of the screen with small motions. The experimental results show that movements of the user's palm within the range of 30 cm ensure movements of the mouse pointer to the edges of the screen.

Electromyographic (EMG) signals have been widely used as motion commands of prosthetic arms. Although EMG signals contain meaningful information including the movement intentions of human body, it is difficult to predict the subject's motion by analyzing EMG signals in real-time due to the difficulties in extracting motion information from the signals including a lot of noises inherently. In this paper, four Ag/AgCl electrodes are placed on the surface of the subject's major muscles which are in charge of four upper arm movements (wrist flexion, wrist extension, ulnar deviation, finger flexion) to measure EMG signals corresponding to the movements. The measured signals are sampled using DAQ module and clustered sequentially. The Fuzzy C-Means (FCMs) method calculates the center values of the clustered data group. The fuzzy system designed to detect the upper arm movement intention utilizing the center values as input signals shows about 90% success in classifying the movement intentions.

It costs high in both memory usage and time consuming to sample the space to compute charge density and calculate electric field on that with large size of plasma data. In real-time and interactive application, accelerating the compute time is critical problem. In this paper, we suggest new method to visualize electric field by using convolution theorem, and the parallel computing to accelerate computing time by using GPGPU. We conduct a simulation that compare running time between the methods with convolution and without convolution. We discussed the method of visualization of multivariate data in three dimensional space using colored volume rendering and surface construction.

The main objective of HACCP(Hazard analysis and critical control points) system is to provide a systematic preventive approach how to control the risks in food production process. Practically, the diet classification process performed at the one of the beginning steps of the HACCP system, makes an important role of determining food safety risks and how to control them in every control point according to the different risk level of the diet. In this paper, we propose an automatic diet classification method for HACCP system using XML(eXtensible Markup Language). In order to guarantee the diet classification accuracy, we design the XML schema and attributes represents the relationship of every diet and ingredients analysing the HACCP diet classification rules. Based on the XML schema and document generation method, we develope the proposed system as client and server model that implemented XML based HACCP diet information generation module and integrated HACCP information management modules, respectively. Moreover, we show the efficiency of the proposed system with experiment results describing the school food diet information as XML documents and parsing the diet information.

Mobile electronic display applications represent a simple motion and express personal motions recently. In this context, we propose the Mobile Signage Application as against these existing applications. It provides the quality motions by multiplex editing and thus should share a kinetic typography with other people using Bluetooth. The Mobile Signage Application includes kinetic motions that are developed by HTML5 and JavaScript to attain variety effects. Furthermore, usability evaluation shows its sufficient availability and serviceability.