• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.4
• /
• pp.580-585
• /
• 2010

In this paper, The object Tracking System is designed by SOPC based Nios II embedded processor and C2H compiler. And this system using single PTZ camera can effectively control IPs in the platform of SOPC based Nios II Embedded Processor and creating IP by C2H(C-To-Hardware) compiler for image-in/output, image-processing and devices of communication that can supply various monitoring information to network or serial. Accordingly, Special quality and processing speed of object tracking using high-quality algorism in the system is improved by hardware/software programming methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.4
• /
• pp.744-751
• /
• 2008

Ubiquitous computing is a new paradigm of telecommunication technology and is embedded with advanced computing technology to process a large amount of data in a normal environment. Generally, ail equipment is embedded with sensors and operating devices to interaction with communication functions. That is why ubiquitous computing must be able to access any devices anywhere at anytime in order to perform appropriate functions. Unfortunately, however, it is difficult to make an optimized design for applications which can effectively interaction with various functions in distributed environment like ubiquitous computing. Therefore, this paper is aimed at deploying interface with server nodules and virtual prototyping by utilizing LabVIEW and embedded application software with additional network function. In addition, given information about sensors collected from context-awareness and location-awareness, it will suggest the ideal ubiquitous application based on context-awareness and apply the advanced application to device control and monitoring through context awareness of lab.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.11
• /
• pp.2179-2184
• /
• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. This paper described appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.2
• /
• pp.247-253
• /
• 2008

In this paper, we describes the design and implementation of real-time management system for efficient operation via monitoring and control of MCC(Motor Control Center). The real-tine management system can be divided hardware(MCC panel) and software(management program). First, hardware is divided into load attaching motor and MCC components for working together control and data network. Second, software(management system) are consisted of communication interface, environment setting, data processing modules. The produced and implemented reduction model of MCC panel is pretested using m-PRO, iM-PRO devices, and HyperTerminal. For field test, MCC panel is tested by RS-232C/485, communication procedure in management system is certified by transmitting and receiving message using control command. By the experimental results, the implemented real-time management system can be used to operate MCC system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.4
• /
• pp.791-799
• /
• 2008

An image recognition for surrounding conditions is very important in image transmission. In recently rears, as the information infrastructure is more general, the user-centered demands in which they want to identify by object's states image using wire or wireless environment have increased. However, existing mobile solution could be hard to expect high quality mage, because limitation of software processing according as network based on mobile terminal which has low band width supports software codec. To solve this weak point, this paper describes on hardware codec design based on MPEG-4 which is international video compression standard. Implemented system contains the embedded CPU for optimized design and it works high quality service as transmission speed and resolution in mobile circumstance.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.154-154
• /
• 2019

Characterization of reliable field-scale root-zone soil moisture (RZSM) variability contribute to effective hydro-meterological monitoring. Although a promising cosmic-ray neutron probe (CRNP) holds the pontential for field-scale RZSM measurement, it is often restricted at deeper depths due to the non-unique sensitivity of CRNP-measured fast neutron signal to other hydrogen pools. In this study, a merging framework relied on coupling cosmic-ray soil moisture with a representative additional RZSM, was introduced to scale shallower CRNP effective depth to represent root-zone layer. We tested our proposed framework over a densely vegetated region in South Korea covering a network of one CRNP and nine in-situ point measurements. In particular, cosmic-ray soil moisture and ancillary RZSM retrieved from the most time stable location were considered as input datasets; whereas the remaining point locations were used to generate a reference RZSM product. The errors between these two input datasets and the reference were forecasted by a linear autoregressive model. A linear combination of forecasts was then employed to compute a suitable weight for merging two input products from the predicted errors. The performance of merging framework was evaluated against reference RZSM in comparison to the two original products and a commonly used exponential filter technique. The results of this study showed that merging framework outperformed other products, demonstrating its robustness in improving field-scale RZSM. Moreover, a strong relationship between the quality of input data and the performance merging framework in light of CRNP effective depth variation has been also underlined via the merging framework.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.32 no.3
• /
• pp.67-91
• /
• 2021

The purposes of this study is to identify the perception of students' use of university libraries' public relations activities using Instagram and propose ways to improve the operation of university libraries' Instagram. To this end, the status of Instagram operations of domestic and foreign university libraries was investigated, and a survey was conducted on 292 students who used the library Instagram of their universities. Based on the research results, first, it is necessary to promote the use of libraries by using 'Library Events' information closely related to the use of Instagram by students, but planning ways to participate that can lead to practical use of libraries. Second, it is necessary to promote the role of librarians through Instagram and utilize daily communication information in order to positively affect library image recognition. Third, it is necessary to guide users on how to inquire on library Instagram and actively respond to communication with users through periodic post uploads and monitoring.

• Journal of Korean Neurosurgical Society
• /
• v.62 no.3
• /
• pp.353-360
• /
• 2019

Epilepsy surgery that eliminates the epileptogenic focus or disconnects the epileptic network has the potential to significantly improve seizure control in patients with medically intractable epilepsy. Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) has been an established option for epilepsy surgery since the US Food and Drug Administration cleared the use of MRgLITT in neurosurgery in 2007. MRgLITT is an ablative stereotactic procedure utilizing heat that is converted from laser energy, and the temperature of the tissue is monitored in real-time by MR thermography. Real-time quantitative thermal monitoring enables titration of laser energy for cellular injury, and it also estimates the extent of tissue damage. MRgLITT is applicable for lesion ablation in cases that the epileptogenic foci are localized and/or deep-seated such as in the mesial temporal lobe epilepsy and hypothalamic hamartoma. Seizure-free outcomes after MRgLITT are comparable to those of open surgery in well-selected patients such as those with mesial temporal sclerosis. Particularly in patients with hypothalamic hamartoma. In addition, MRgLITT can also be applied to ablate multiple discrete lesions of focal cortical dysplasia and tuberous sclerosis complex without the need for multiple craniotomies, as well as disconnection surgery such as corpus callosotomy. Careful planning of the target, the optimal trajectory of the laser probe, and the appropriate parameters for energy delivery are paramount to improve the seizure outcome and to reduce the complication caused by the thermal damage to the surrounding critical structures.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.2
• /
• pp.97-106
• /
• 2019

Today, many smart sensor's measurement instruments are used to check the safety situation of various medium and large bridge structures that should be maintained in the construction facilities, but most of them use the method of measuring and confirming the displacement behavior of the bridge at regular intervals. In order to continuously check the safety situation, various measuring instruments are used, but most of them are not able to measure and measure the displacement and behavior of main construction structures at regular intervals. In this study, GNSS and environment smart sensors and drone's image data are transmitted to wireless network so that risk of many bridge's structures can be detected beforehand. As a result, by diagnosing the fine displacement of the bridge in real time and its condition, reinforcement, repair and disaster prevention measures for the structural parts of the bridges, which are expected to be dangerous, and various disasters and accidents can be prevented, and disaster can be prevented could suggest a new alternative.

• Nuclear Engineering and Technology
• /
• v.51 no.3
• /
• pp.807-817
• /
• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.