• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.12
• /
• pp.152-158
• /
• 2016

In this paper, we implemented the full stack platform design with MongoDB database of open source platform Raspberry PI 3 model. We experimented the triggering of event driven with acceleration sensor data logging with wireless communication. we captured the image of USB Camera(MS LifeCam cinema) with 28 frames per second under the Linux version of Raspbian Jessie and extended the functionality of wireless communication function with Bluetooth technology for the purpose of making Android Mobile devices interface. And therefore we implemented the functions of the full stack platform for recognizing the event triggering characteristics of detecting the acceleration sensor action and gathering the temperature and humidity sensor data under IoT environment. Especially we used MEAN Stack for developing the performance of full stack platform because the MEAN Stack is more akin to working with MongoDB than what we know of as a database. Afterwards, we would enhance the performance of full stack platform for IoT clouding functionalities and more feasible web design with MongoDB.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.7
• /
• pp.81-89
• /
• 1999

Image obtained by incomplete communication always include noise, blur and distortion, etc. In this paper, we propose and apply the new spatial filter algorithm, called an optimal adaptive generalized stack filter(AGSF), which optimizes adaptive generalized stack filter(AGSF) using neural network weight learning algorithm of back-propagation learning algorithm for improving noise removal and edge preservation rate. AGSF divides into two parts: generalized stack filter(GSF) and adaptive multistage median filter(AMMF), GSF improves the ability of stack filter algorithm and AMMF proposes the improved algorithm for reserving the sharp edge. Applied to neural network theory, the proposed algorithm improves the performance of the AGSF using two weight learning algorithms, such as the least mean absolute(LAM) and least mean square (LMS) algorithms. Simulation results of the proposed filter algorithm are presented and discussed.

• Journal of Korea Multimedia Society
• /
• v.20 no.5
• /
• pp.808-826
• /
• 2017

Most of conventional DSS's(Digital Signage Systems) have been built based on LAMP framework. Recent researches have shown that MEAN or MERN stack framework is simpler, more flexible, faster and more suitable for web-based application than LAMP stack framework. In this paper, we propose a design and implementation of MEARN (ME(A+R)N) stack-based real-time digital signage system, MR-DSS, which supports handing real-time tasks like urgent/instant messaging, system status monitoring and so on, efficiently in addition to conventional digital signage CMS service tasks. MR-DSCMS, CMS of MR-DSS, is designed to provide most of its normal services by REST APIs and real-time services like urgent/instant messaging by Socket.IO base under MEARN stack environment. In addition to architecture description of components composing MR-DSS, design and implementation issues are clarified in more detail. Through experimental testing, it is shown that 1) MR-DSS works functionally well, 2) the networking load performance of MR-DSCMS's REST APIs is better compared to a well-known open source Xibo CMS, and 3) real-time messaging via Socket.IO works much faster than REST APIs.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.3
• /
• pp.1-9
• /
• 2015

In this paper, we implemented the computer vision platform design with MEAN Stack through Raspberry PI 2 model which is an open source platform. we experimented the face recognition, temperature and humidity sensor data logging with WiFi communication under Raspberry Pi 2 model. Especially we directly made the shape of platform with 3D printing design. In this paper, we used the face recognition algorithm with OpenCV software through haarcascade feature extraction machine learning algorithm, and extended the functionality of wireless communication function ability with Bluetooth technology for the purpose of making Android Mobile devices interface. And therefore we implemented the functions of the vision platform for identifying the face recognition characteristics of scanning with PI camera with gathering the temperature and humidity sensor data under IoT environment. and made the vision platform with 3D printing technology. Especially we used MongoDB for developing the performance of vision platform because the MongoDB is more akin to working with objects in a programming language than what we know of as a database. Afterwards, we would enhance the performance of vision platform for clouding functionalities.

• 전기의세계
• /
• v.26 no.2
• /
• pp.95-98
• /
• 1977

Commercially available fuel oil for power plant contains relatively much sulphur, which means accordingly high content sulphur deoxide in exhaust gas. Sulphur deoxide has been identified as the worst-pollutant caused by thermal power generation. This paper primarily deals with the stack gas diffusion effects of various parameters, namely vertical stability, wind velocity, exhaust gas velocity, stack height, etc., on the ground concentration. thereof the relation between stack height and maximum plant capacity is analyzed from the standpoint of air pollution prevention. The limit capacity is calculated by means of mean concentration introducing Mead and Lowry coefficient respectively.

• Journal of Korean Society for Quality Management
• /
• v.22 no.4
• /
• pp.79-101
• /
• 1994

In modern manufacturing, a product consists of many components created by different processes. Variations in the individual component dimensions and in the processes may result in unacceptable final assemblies. Thus, engineers have increased pressure to properly set tolerance specifications for individual components and to control manufacturing processes. When a proper variation stack-up analysis is not performed for all of the components in a functional system, all component parts can be within specifications, but the final assembly may not be functional. Thus, in order to improve the performance of the final assembly, a proper variation stack-up analysis is essential for specifying dimensional tolerances and process control. This research provides a detailed case example of the use of variation stack-up analysis using a Monte Carlo simulation method to improve the defect rate of a complex process, which is the commutator brush track undercut process of an armature assembly of a small motor. Variations in individual component dimensions and process mean shifts cause high defect rate, Since some dimensional characteristics have non-normal distributions and the stack-up function is non-linear, the Monte Carlo simulation method is used.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.2
• /
• pp.88-95
• /
• 1999

Stack filters are a class of digital nonlinear filters with excellent properties for signal restoration. Unfortunately, present algorithms for designing stack filters with large window size are limited in applications by their computational overhead and serial nature. In this paper, new, highly-parallel algorithm is developed for determining a stack filter which minimizes the mean absolute error criterion. It retains the iterative nature of the present adaptive algorithm, but significantly reduces the number of required to converge to an optima filter. A proof is also give that the proposed algorithm converges to an optimal stack filter.

• Asian Journal of Atmospheric Environment
• /
• v.2 no.1
• /
• pp.1-13
• /
• 2008

A numerical simulation method has been developed to predict atmospheric flow and stack gas diffusion using a calculation domain of several km around a stack under complex terrain conditions containing buildings. The turbulence closure technique using a modified k-$\varepsilon$-type model under a non hydrostatic assumption was used for the flow calculation, and some of the calculation grids near the ground were treated as buildings using a terrain-following coordinate system. Stack gas diffusion was predicted using the Lagrangian particle model, that is, the stack gas was represented by the trajectories of released particles. The numerical model was applied separately to the flow and stack gas diffusion around a cubical building and to a two-dimensional ridge in this study, before being applied to an actual terrain containing buildings in our next study. The calculated flow and stack gas diffusion results were compared with those obtained by wind tunnel experiments, and the features of flow and stack gas diffusion, such as the increase in turbulent kinetic energy and the plume spreads of the stack gas behind the building and ridge, were reproduced by both calculations and wind tunnel experiments. Furthermore, the calculated profiles of the mean velocity, turbulent kinetic energy and concentration of the stack gas around the cubical building and the ridge showed good agreement with those of wind tunnel experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.422-424
• /
• 2009

In this paper, we studied methods that measure chip stack height using slit beam in mold equipment among semiconductor manufacture equipments. We studied two methods to improve chip stack height measurement performance. First, it is relation of camera exposure time and height measurement repeatability. Second we could improve measurement performance applying method of least mean square method for measurement error minimization about PCB(Printed Circuit Board) flexure phenomenon.

• Journal of Environmental Science International
• /
• v.25 no.1
• /
• pp.155-161
• /
• 2016

In this study, field experiment, odor simulator, and dispersion modeling were used to evaluate the odor impact from J sewage sludge treatment facility. The height and flow rate of exhaust stack at this facility were 22.3 m and $100Nm^3/min$. The mean odor concentrations of the wet scrubber inlet and exhaust stack were $267{\pm}160$ and $93{\pm}44OU/m^3$, respectively. The odor removal efficiency of wet scrubber showed 65%. The odor simulator is used for the regulated standard calculation of the exhaust pipe(stack). Resulting odor emission rate(OER) by odor simulator was $2.4{\times}10^6(24,000OU/m^3)$. The forecasting result by Screen3 modeling showed that odor exhaust concentration up to $30,000OU/m^3$ was't exceeded maximum allowable emission level on site boundary($15OU/m^3$).