Simultaneous pattern measurement system is new research subject for OLED panel inspection. It is defect inspection of OLED panel after deposition. This research suggests the system that calculates the size and center point of each patterns after obtaining standard and deposition pattern as one image. This system could be applied to OLED manufacturing process. The research result shows that the size and center point of each patterns could be obtained by displaying the standard pattern and deposition pattern in one image.

This paper presents a deep learning-based object detection method for recognizing vehicles in images acquired through cameras installed on ceiling of underground parking lot. First, we present an image enhancement method, which improves vehicle detection performance under dark lighting environment. Second, we present a new CNN-based multiscale classifiers for detecting vehicles in images acquired through cameras with fisheye lens. Experiments show that the presented vehicle detector has better performance than the conventional ones.

The crowded environment of a domestic pig farm is highly vulnerable to the spread of infectious diseases such as foot-and-mouth disease, and studies have been conducted to automatically analyze behavior of pigs in a crowded pig farm through a video surveillance system using a camera. Although it is required to correctly separate occluding pigs for tracking each individual pigs, extracting the boundaries of the occluding pigs fast and accurately is a challenging issue due to the complicated occlusion patterns such as X shape and T shape. In this study, we propose a fast and accurate method to separate occluding pigs not only by exploiting the characteristics (i.e., one of the fast deep learning-based object detectors) of You Only Look Once, YOLO, but also by overcoming the limitation (i.e., the bounding box-based object detector) of YOLO with the test-time data augmentation of rotation. Experimental results with two-pigs occlusion patterns show that the proposed method can provide better accuracy and processing speed than one of the state-of-the-art widely used deep learning-based segmentation techniques such as Mask R-CNN (i.e., the performance improvement over Mask R-CNN was about 11 times, in terms of the accuracy/processing speed performance metrics).

In this paper, we propose a character floating hologram system using the user's gender and age. The proposed system recognizes the gender and age of the user through depth images and color images. The depth images are used to find and normalize facial position. Next, by using facial color images, the age and gender are estimated through an verified database-based model of CNN. Finally, the estimated age and gender are expressed to a character for the floating hologram. The proposed system can be used in a variety of areas, including marketing, advertising, and exhibition events using gender or age.

With the development of medical technology, interest in rehabilitation devices is increasing and various devices are being studied. In particular, devices for speech disorders such as hearing impairment and cleft palate are attracting attention. In general, the nasometer is used for patients with flaccid dysarthria and velopharyngeal incompetence(VPI). However, in the case of the conventional separator type nasometer, that has an acoustic feedback problem between the oral and nasal sounds. In recent, the mask type nasometer has been developed which is insensitive to acoustic feedback. But, still not popularized. In this paper, the nasometer characteristics of the conventional separation type and mask type are analyzed. Also, We were obtained clinical acoustic data from the 6 subjects and examined the significant differences in the structure of the separation type and mask type nasometer. Through experiments, it was confirmed that the measurement was about 3~15% higher in the mask type nasometer than the conventional nasometer having a separator type. Also, We was considered the necessity of nasometer signal processing for acoustic feedback reduction and nasalance calculation optimization.

Even though so much progresses have been achieved in Multiple Object Tracking (MOT), most of reported MOT methods are not still satisfactory for commercial embedded products like Pan-Tilt-Zoom (PTZ) camera. In this paper, we propose a real-time multiple pedestrians tracking method for embedded environments. First, we design a new light weight convolutional neural network(CNN)-based pedestrian detector, which is constructed to detect even small size pedestrians, as well. For further saving of processing time, the designed detector is applied for every other frame, and Kalman filter is employed to predict pedestrians' positions in frames where the designed CNN-based detector is not applied. The pose orientation information is incorporated to enhance object association for tracking pedestrians without further computational cost. Through experiments on Nvidia's embedded computing board, Jetson TX2, it is verified that the designed pedestrian detector detects even small size pedestrians fast and well, compared to many state-of-the-art detectors, and that the proposed tracking method can track pedestrians in real-time and show accuracy performance comparably to performances of many state-of-the-art tracking methods, which do not target for operation in embedded systems.

Recently, due to the rapid growth of the internet the existing network architecture is showing limitations. In order to overcome these problems SDN has been proposed as a new paradigm. EIGRP is a modern routing protocol with many advantages but little research has been done on operation in SDN. In this paper we propose a controller-centric EIGRP based on the SDN environment. To construct the SDN network, We seperate the control function and the data transfer function and the EIGRP is operated by a separated controller. Experiments have shown that the proposed scheme can actually work and be used effectively.

Visible light communication technology is being studied and developed in various ways due to advantages such as high transmission speed, excellent positioning and higher security. However, existing visible light communication systems have difficulties in entering the market because they use special transmitters and receivers. We will overcome the difficulty if we develope a VLC system that uses a conventional LED light as a transmitter and a smartphone camera as a receiver. What matters is that LED lights include a scatter filter to prevent glareness for human eyes, but the existing VLC(Visual Light Communication) method can not be applied. In this paper, we propose a method to encode data with On / Off patterns of LEDs in the lighting with $M{\times}N$ LEDs. We defined parameters like L-off-able and K-seperated to facilitate the recognition of On / Off patterns in the diffused Lights. We conducted experiments using an LED lighting and smart phones to determine the parameter values. Also, the maximum transmission rate of our encoding technique is mathematically presented. Our encoding scheme can be applied to indoor and outdoor positioning applications or settlement of commercial transactions.

In the information society represented by the Fourth Industrial Revolution, various types of data and information that are difficult to see are produced, processed, and processed and circulated to enhance the value of existing goods. The IoT(Internet of Things) paradigm will change the appearance of individual life, industry, disaster, safety and public service fields. In order to implement the IoT paradigm, several elements of technology are required. It is necessary that these various elements are efficiently connected to constitute one system as a whole. It is also necessary to collect, provide, transmit, store and analyze IoT data for implementation of IoT platform. We designed and implemented a big data processing IoT platform for IoT service implementation. Proposed platform system is consist of IoT sensing/control device, IoT message protocol, unstructured data server and big data analysis components. For platform testing, fixed IoT devices were implemented as solar power generation modules and mobile IoT devices as modules for table tennis stroke data measurement. The transmission part uses the HTTP and the CoAP, which are based on the Internet. The data server is composed of Hadoop and the big data is analyzed using R. Through the emprical test using fixed and mobile IoT devices we confirmed that proposed IoT platform system normally process and operate big data.

The performance of an intelligent classifier for detecting malwares added to multimedia contents based on machine learning is highly dependent on the properties of feature set. Especially, in order to determine the malicious code in real time the size of feature set should be as short as possible without reducing the accuracy. In this paper, we introduce an optimal feature selection method to satisfy both high detection rate and the minimum length of feature set against the feature set provided by PEFeatureExtractor well known as a feature extraction tool. For the evaluation of the proposed method, we perform the experiments using Windows Portable Executables 32bits.

Given a positive integer k as input, a spatial preference query finds the k best data objects based on the scores (e.g., qualities) of feature objects in their spatial neighborhoods. Several solutions have been proposed for spatial preference queries in Euclidean space. A few algorithms study spatial preference queries in undirected spatial networks where each edge is undirected and the distance between two points is the length of the shortest path connecting them. However, spatial preference queries have not been thoroughly investigated in directed spatial networks where each edge has a particular orientation that makes the distance between two points noncommutative. Therefore, in this study, we present a new method called ALPS+ for processing spatial preference queries in directed spatial networks. We conduct extensive experiments with different setups to demonstrate the superiority of ALPS+ over conventional solutions.

There are several methods which efficiencies of database are uprise. One of the well-known methods is that segments of database satisfying a query was rapidly accessed and processed. So if it is possible to search completely parallel multiple database segment types which satisfy a query, the response time of the query will be reduced. The matter of obtaining CPS(Completely Parallel Searchable) distribution without redundancy can be viewed as graph theoretic problem, and the operation of ring sum on the graph is used for CPS. In this paper, the parallel algorithm is proposed.

Bulk-loading an R-tree can be a good approach to build an efficient one. However, it takes a lot of time to bulk-load an R-tree for huge amount of data. In this paper, we propose a parallel R-tree construction scheme based on a Hadoop framework. The proposed scheme divides the data set into a number of partitions for which local R-trees are built in parallel via Map-Reduce operations. Then the local R-trees are merged into an global R-tree that covers the whole data set. While generating the partitions, it considers the spatial distribution of the data into account so that each partition has nearly equal amounts of data. Therefore, the proposed scheme gives an efficient index structure while reducing the construction time. Experimental tests show that the proposed scheme builds an R-tree more efficiently than the existing approaches.

Old people and patients with cardiovascular disease could die of a heart attack in the bath with heated water for a long time. Various researches have been studied to prevent these accidents from happening such as measuring the ECG signal when taking bath. However, these devices are hard to use and the higher price is not easily accepted by the public. In this paper, a low-cost and use-friendly, real time high precision water temperature monitoring device to prevent heart attack in the bath was developed. The device with waterproof design that lets the device can float on the surface of the water, and an accurate way to make water temperature measurement method was proposed by this paper that is immerging the sensor into water with 4cm depth to measure the temperature of underwater. The manufactured device was conducted to two experiments; one was to verify the basic functions of the device, and another one was for compare the proposed device with commercial products for monitoring the water temperature in the bathtub. As the experimental results shown, the proposed device has stable performance for the water temperature measurement and communicating with laptop in wireless.

Big data processing technology and artificial intelligence (AI) are increasingly attracting attention. Natural language processing is an important research area of artificial intelligence. In this paper, we use Korean news articles to extract topic distributions in documents and word distribution vectors in topics through LDA-based Topic Modeling. Then, we use Word2vec to vector words, and generate a weight matrix to derive the relevance SCORE considering the semantic relationship between the words. We propose a way to recommend documents in order of high score.

As the growth of developing Islamic countries, Muslims are into the world. The most important thing for Muslims to purchase food, ingredient, cosmetics and other products are whether they were certified as 'Halal'. With the increasing number of Muslim tourists and residents in Korea, Halal restaurants and markets are on the rise. However, the service that provides information on Halal restaurants and markets in Korea is very limited. Especially, the application of recommendation system technology is effective to provide Halal restaurant information to users efficiently. The profiling of Halal restaurant information should be preceded by design of recommendation system, and design of recommendation algorithm is most important part in designing recommendation system. In this paper, an Intelligent Recommendation Service system for offering Halal food (IRSH) based on dynamic profiles was proposed. The proposed system recommend a customized Halal restaurant, and proposed recommendation algorithm uses hybrid filtering which is combined by content-based filtering, collaborative filtering and location-based filtering. The proposed algorithm combines several filtering techniques in order to improve the accuracy of recommendation by complementing the various problems of each filtering. The experiment of performance evaluation for comparing with existed restaurant recommendation system was proceeded, and result that proposed IRSH increase recommendation accuracy using Halal contents was deducted.

Recently, hearing loss patients have been increasing to excessive use of various multimedia devices. One of the hearing rehabilitation systems, bone conduction hearing aid can be used to conductive deafness patients efficiently. However, the conventional bone conduction hearing systems has some problems such as skin diseases, repulsion of patients, and vibration power reduction by skin damping. In this paper, to overcome the conventional problems, we proposed power improvement method by curved beam diaphragm. The proposed method is skin attachment system which is non-implantable, and then the power of transducer is improved by the proposed method. In order to improve the vibration power of diaphragm, variable that has correlation with displacement are extracted, the diaphragm designed by extracted variable. To verify efficient of the proposed method, experiment conducted by finite element analysis. As a result of, the proposed method confirmed improved power to compare with the conventional method and proposed method.

In order to reflect complex and diverse building types, resident characteristics and disaster factors, it is necessary to introduce a flexible situation-based response system based on real-time information. Intelligent CCTV, hybrid sensor, location scanner, and customized broadcasting device were examined to introduce for the real-time response intelligent response system and its feasibility was verified through field test. In addition, based on the real-time information, the evacuation simulation was executed by assuming the dormitory building and the resident of the school, and the safety of the evacuation and the shortening of the pinnacle time were confirmed. The feasibility of real time information based evacuation comparing with the existing evacuation system were verified in the case of evacuation.

Mobile-based software development methodology has been vigorously researched from using object-oriented development methodology and component-based development methodology previous structural developing methodology. There are two types of OS in mobile platform which are android and iOS. There is a problem that the application to be developed is developed depending on the device type. To resolve this problem, first, the system structure and design method should be managed effectively. Second, a basic design guide that can be commonly adapted to the each project is required. In this paper, we define a mobile cross platform meta model based on MDA-development methodology, focusing on reusability, portability and interoperability about non - dependent part of the mobile platform. If the proposed meta-model is applied to manage the related information and all the types of Mobile-Apps become available through independent mobile app development process, henceforward, it will be much of help establishing formulaic mobile-app developmental methodology.

Most web documents are written in Cartesian coordinates, so the study of vertical arrangement of text has been well organized, while the study of circular arrangement is very early. With the recent development of circular display devices, the demand for circular arrangement of texts is increasing. Thus, we proposed a CSS3 extended specification of polar coordinate layout for the circular placement of text. First, we defined the concept of fan model for the text arrangement in polar coordinate which is corresponding to box model in Cartesian coordinate. And, we described new definition on the directions of sentence, paragraph and text orientation in polar coordinate. Based on this new definitions, we developed the extended specification consisting of three parts. A part for setting the fan model, a part for setting directions, and a part for setting typesetting properties. To verify the feasibility of the proposed specification in current web browsers, a preprocessor was developed and sample contents were examined. We compared the code length of the sample contents implemented using other JavaScript library CssWarp.js so as to verify the efficiency of the proposed specification.

Virtual reality applications in Head-Mounted Displays require high frame rates and low latency rendering techniques. Ray tracing offers many benefits, such as high-quality image generation, but has not been utilized due to lower performance than rasterization. But that can obtain good result combined with gaze-tracking technology and human visual system's operation principle. In this paper, we propose a method to optimize the foveated sampling map and to maintain the visual quality through the fast voronoi nearest interpolation. The proposed method further reduces the computational cost that has been improved by the previous foveated sampling. It also smoothes the voronoi boundary using adaptive sibson interpolation, which was not possible in real-time. As a result, the proposed method can render real-time high-quality images with low visual difference.

After the launch of smart phones, various miniaturized smart devices such as wearable and IOT devices have deeply embedded in human life, and have created a technology-oriented society. In this technology-oriented society, technology development itself is important, however it seems more important to utilize existing technology appropriately and deliver effectively to human life. As the computer became personalized after the appearance of PC, human-centered computing such as HCI and UCD had begun to appear. However, most of the researches focused on technology that made human being convenient to interact with computer such as computer systems design and UX development. In the technology-oriented society, it seems more urgent to apply existing technology to human life. In this paper, we propose a methodology, 'Digital Leveraging' which guides how to effectively apply technology to human life. Digital Leveraging is the way of convergence between technology and humanities.