• ETRI Journal
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• v.35 no.2
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• pp.301-310
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• 2013

Nowadays, the multicore processor is watched with interest by people all over the world. As the design technology of system on chip has developed, observing and controlling the processor core's internal state has not been easy. Therefore, multicore processor debugging is very difficult and time-consuming. Thus, we need a reliable and efficient debugger to find the bugs. In this paper, we propose an on-chip debug architecture for multicore processors that is easily adaptable and flexible. It is based on the JTAG standard and supports monitoring mode debugging, which is different from run-stop mode debugging. Compared with the debug architecture that supports the run-stop mode debugging, the proposed architecture is easily applied to a debugger and has the advantage of having a desirable gate count and execution cycle. To verify the on-chip debug architecture, it is applied to the debugger of the prototype multicore processor and is tested by interconnecting it with a software debugger based on GDB and configured for the target processor.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.2
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• pp.160-164
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• 2022

In this paper, through the development of a smart panel (LCD kiosk) controller, contents to develop a system that can be operate in a desired environment by operating the window control and ventilation facilities according to the automatic controller operation based on the set values such as temperature, humidity, sunlight, and rainfall. In particular, the MQTT protocol-based sensor module can be directly manufactured and applied at any time based on various communication and power sources such as wireless, wired, and PLC (power line communication) to obtain the desired data, as well as fire, power failure, and intrusion in the house. It is also a system that enables operation and monitoring from a remote location based on the cloud environment by connecting sensors. Kiosks are currently being used in many places, and the demand for them is on the rise, and an active influx of young people can be expected through environmental improvement. It is expected to increase interest and understanding for improvement.

• Advances in nano research
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• v.12 no.4
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• pp.375-386
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• 2022

Synthesis of acrylate-based dispersion resins involves many parameters including temperature, ingredients concentrations, and rate of adding ingredients. Proper controlling of these parameters results in a uniform nano-size chain of polymer on one side and elimination of hazardous residual monomer on the other side. In this study, we aim to screen the process parameters via Internet of Things (IoT) to ensure that, first, the nano-size polymeric chains are in an acceptable range to acquire high adhesion property and second, the remaining hazardous substance concentration is under the minimum value for safety of public and personnel health. In this regard, a set of experiments is conducted to observe the influences of the process parameters on the size and dispersity of polymer chain and residual monomer concentration. The obtained dataset is further used to train an Adaptive Neural network Fuzzy Inference System (ANFIS) to achieve a model that predicts these two output parameters based on the input parameters. Finally, the ANFIS will return values to the automation system for further decisions on parameter adjustment or halting the process to preserve the health of the personnel and final product consumers as well.

• Journal of Dairy Science and Biotechnology
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• v.26 no.2
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• pp.45-49
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• 2008

We studied the feasibility of monitoring and controlling the manufacturing process of an infant formula with rice starch by testing in-process samples using rheology. We used DSC to first determine the gelatinization temperature of the rice starch, a key ingredient of this product. With this characteristic temperature and the process design known, rheological measurements were conducted on the in-process samples for detecting the presence and extent of gelatinization and retrogradation of rice starch; in-process samples were collected from the carbohydrate tank, after the homogenizer, and the finished product tank. The correlation between the rheological measurements on these samples and manufacturing performance proved that rheology is a very sensitive tool for monitoring the structural development of this infant formula during main process, and their influence on sterilization efficiency. We observed that the lower degree of gelatinization during main process, a shorter residence time in the finished product tank, and using caustic flush rather than clean-in-place additively lead to higher sterilization efficiency. These findings can be utilized for a rational design and analysis of the manufacturing process for infant formulas containing rice starch.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.58-65
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• 2011

Construction Productivity is one of the most important elements in construction management. It is used in construction process scheduling and cost management, which are significant sector in construction management. It is important to make appropriate schedule and monitor how works are done within schedule. But construction project contains uncertainty and inexactitude, modifying construction schedule is being an issue to manage construction works well. Even though prediction and monitoring of productivity can be principal activity, it is hard to predict productivity with manager's experience and a standard of estimate. A large number of factors influencing productivity, such as drawing, construction method, weather, labor, material, equipment, etc. But current calculation of productivity depends on empirical probability, not consider difference of each influencing factor. In this research, the aim is to present a productivity predicting regression model of form work, which includes effectiveness of influences factors. 5 variables existed inside form work are selected by interview and site research based on literature review of existed various productivity influencing factors. The effectiveness and correlation of productivity influencing factors are analyzed by statistical approach, and it is used to make productivity regression model. The finding of this research will improves monitoring and controlling of project schedule in construction phase.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.210-218
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• 2006

Traditional statistical process control (SPC) applied to discrete part industry in the form of control charts can look for and eliminate assignable causes by process monitoring. On the other hand, engineering process control (EPC) applied to the process industry in the form of feedback control can maintain the process output on the target by continual adjustment of input variable. This study presents controlling and monitoring rules adopted by variable sampling interval (VSI) to change sampling intervals in a predetermined fashion on the predicted process levels under integrated EPC and SPC systems. Twelve rules classified by EPC schemes(MMSE, constrained PI, bounded or deadband adjustment policy) and type of sampling interval combined with EWMA chart of SPC are proposed under IMA (1,1) disturbance model and zero-order (responsive) dynamic system. Properties of twelve control rules under three patterns of process change (sudden shift, drift and random shift) are evaluated and discussed through simulation and control rules for integrated VSI EPC and SPC systems are recommended.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1239-1246
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• 2004

The integration and union of regional digital map and vehicle location data in e-Logistics which means virtual service architecture based on the Internet among the logistics companies is indispensable clause in order to satisfy the visibility characteristics. Most conventional vehicle monitoring and controlling systems were constructed with individual and mutual exclusive architecture so that there are required lots of cost for sharing and integrating the information among them. In this paper, we design and implement an component-based open system which represent moving object location information as well as digital map using the GML(Geography Markup Language - international standard encoding based on XML). We also test proposed system on the delivery vehicle scenario in e-Logistics environment, and validate its superior in terms of extensibility and interoperability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.283-284
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• 2021

The domestic and overseas IoT (Internet of Things)-based automation industry is developing remarkably, and the development of this automation technology is further accelerated by the development of sensor technology. In recent years, the smart farm industry for the purpose of growing crops based on various sensor technologies is rapidly developing. In the case of smart farms, real-time monitoring and mobile services are provided by measuring representative environmental data such as temperature, humidity, and CO2 required for crop cultivation. Most of these environmental monitoring and control operations use the RS-485-based Modbus (RTU) communication method. In this paper, we intend to test the performance of sensor data and actuator information required for smart farm construction by building a platform for controlling sensor data and actuators based on LabView using MQTT (Message Queuing Telemetry Transport), an IoT standard protocol.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.1-6
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• 2021

Currently, virus infection such as Corona 19 has become commonplace, and interest in unmanned systems is increasing in the field for non-face-to-face ICT services. In this paper, the function and performance of remotely successfully controlling a store through video and audio using an IP PBX with a broadcasting function was verified through a test. And the fully unmanned system is not gaining credibility due to various technical problems, however the central control system is a very efficient and reliable system because the controller can directly control the customer while monitoring the access and the inside of the store through the video and audio. In the future, we plan to study a completely unmanned remote control system using A.I technology.