• Smart Media Journal
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• v.3 no.4
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• pp.35-40
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• 2014

As small sized bio-sensors and digital yarns are developed, digital wear measuring vital signs can be used for individuals' health, the elderly care and sports activities. This paper discusses a database structure for analyzing stress state, pulses, positions, exercise amount of user based on vital signs measured for 24 hours measured by the wear and GPS information, and a storage for storing XML documents following a standard HL7 meta-model. By analyzing the stored information, the system identifies the stress state and exercise amount of users. Pulses, exercise intensity and emergency situations can be also detected by the system in real time. This paper discusses the implementation of a system enabling to acquire and analyze vital signals to understand user behavior patterns.

• Speech Sciences
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• v.10 no.4
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• pp.41-55
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• 2003

This paper investigates the tonal patterns of English information structure composed of topic and focus. It has been argued in previous theories that there is a significant relationship between English topic-focus structure and intonation. The English topic is marked with L+H* pitch accent and focus is marked with H* pitch accent. These theories, however, are oversimplified ones since they do not consider the contextual differences of topic and focus. To examine more concrete tonal patterns of English topic and focus, we classified topic into two subcategories of reminding topic and old-information topic. Focus was categorized into three: information focus, contrastive focus, and reference focus. The overall results show that native English speakers are inclined to use both the L+H* and H* pitch accent for the topic and focus of an utterance. We also observe a tendency to deaccentuate the topics given as old information and to mark the topics given as noun phrase with H* pitch accent. As for the intonation of focus, H* pitch accent is the most frequent type of accent, but L+H* also shows a high percentage of implementation especially in the context of correction or contrast.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.6
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• pp.545-555
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• 1991

In this paper, We discuss optical implementation of new optical adaptive patern recognition system based on single layer perception with learning capability and associative memory model having error corrective capability. The single layer perceptron is optically implemented by using 2 D LCTV spatial light modulators through the nonlinear quantization and polarization encoding methods, and 2 D hopfield associative memory is also implemented by using multifocus holographic lens. From some experimental results on classfication of Arabic numbers into even & edd numbers, it is shown that the proposed system can classify the patterns to the right classes correctly even for the partial and erronenous input patterns. Accordingly, the proposed optical adaptive pattern recognition system can be suggested for practical application in the fields of image processing and pattern recognition.

• Spatial Information Research
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• v.19 no.1
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• pp.127-133
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• 2011

Recently, with the advances in sensor techniques and net work computing, Ubiquitous Sensor Network (USN) has been received a lot of attentions from various communities. The sensor nodes distributed in the sensor network tend to continuously generate a large amount of data, which is called stream data. Sensor stream data arrives in an online manner so that it is characterized as high-speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. The data stream has many application domains such as traffic analysis, physical distribution, U-healthcare and so on. Therefore, there is an overwhelming need of a USN middleware for processing such online stream data to provide corresponding services to diverse applications. In this paper, we propose a novel USN middleware which can provide users both context-aware service and meaningful sequential patterns. Our proposed USN middleware is mainly focused on location based applications which use stream location data. We also show the implementation of our proposed USN middleware. By using the proposed USN middleware, we can save the developing cost of providing context aware services and stream sequential patterns mainly in location based applications.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1388-1391
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• 2010

In this paper, we present a design and implementation of U-learning system using pen based augmented reality approach. Student has been given a smart pen and a smart study book, which is similar to the printed material already serviced. However, we print the study book using CMY inks, and embed perceptually invisible dot patterns using K ink. Smart pen includes (1) IR LED for illumination, IR pass filter for extracting the dot patterns, and (3) camera for image captures. From the image sequences, we perform topology analysis which determines the topological distance between dot pixels, and perform error correction decoding using four position symbols and five CRC symbols. When a student touches a smart study books with our smart pen, we show him/her multimedia (visual/audio) information which is exactly related with the selected region. Our scheme can embed 16 bit information, which is more than 200% larger than previous scheme, which supports 7 bits or 8 bits information.

• Journal of KIBIM
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• v.13 no.3
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• pp.12-20
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• 2023

Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.6
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• pp.43-51
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• 2004

An optical parallel modified signed-digit(MSD) number adder system is proposed by using triple rail-coding input patterns and serial arrangement method of symbolic substitution. By combing overlapped arithmetic results. which are produced by encoding MSD input as triple rail-coding patterns. into the same patterns, symbolic substitution rules are reduced and also by using serialized and space-shifted input patterns in optical experiments, the optical adder without space-shifting operation, NOR operation and threshold operation is implemented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1739-1747
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• 1994

This study is concerned with a feeding method of microstrip patch antennas with different widths as feeding elements in order to obtain the appropriate radiation patterns of nonuniform array antennas. We analyze a microstrip patch antenna based on the transmission line model and derive that the ratio of current is equal to that of the input impedances of array antenna elements in case that the feed-line length between elements of array antenna is equal to the integer times of $\lambda_g$. We measure the radiation patterns of the nonuniform microstrip patch array antenna with 6 and 9 elements. The patterns measured are well agreed with the theoritically calculated patterns. Thus, this result can be utilized in the implementation of a feed network in nonuniform array antennas.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.316-321
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• 2008

Advanced computer network technology enables computers to be connected in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, which makes it vulnerable to previously unidentified attack patterns and variations in attack and increases false negatives. Intrusion detection and analysis technologies are thus required. This paper investigates the asymmetric costs of false errors to enhance the performances the detection systems. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of anomaly traffic detection is enhanced by considering the costs of false errors.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.555-561
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• 2014

Artificial intelligence in the game is mainly used to determine patterns of behavior of NPC (Non Player Character) and the enemy, path finding. These artificial intelligence is implemented by FSM (Finite State Machine) or Flocking method. The number of NPC behavior in FSM method is limited by the number of FSM states. If the number of states is too small, then NPC player can know the behavior patterns easily. On the other hand, too many implementation cases make it complicated. The NPC behaviors in Flocking method are determined by the leader's decision. Therefore, players can know easily direction of movement patterns or attack pattern of NPCs. To overcome these problem, this paper proposes agonistic behaviors(attacks, threats, showing courtesy, avoidance, submission)in animals to apply for the NPC, and implements agonistic behaviors using Unity3D engine. This paper can help developing a real sense of the NPC artificial intelligence.