The similarity detection to plagiarism or duplication of computer programs requires a different type of analysis methods and tools according to the programming language used in the implementation and the sort of code to be analyzed. In recent years, the similarity appraisal for the object code in the embedded system, which requires a considerable resource along with a more complicated procedure and advanced skill compared to the source code, is increasing. In this study, we described a method for analyzing the similarity of functional units in the assembly language through the conversion of object code using the reverse engineering approach, such as the reverse assembly technique to the object code. The instruction and operand table for comparing the similarity is generated by using the syntax analysis of the code in assembly language, and a tool for detecting the similarity is designed.
A deep recursive bidirectional Cuda Deep Neural Network Long Short Term Memory (Bi-CuDNNLSTM) layer is recruited in this paper to predict the entire force time histories, and the corresponding hysteresis and backbone curves of reinforced concrete (RC) bridge piers using experimental fast and slow cyclic tests. The proposed stacked Bi-CuDNNLSTM layers involve multiple uncertain input variables, including horizontal actuator displacements, vertical actuators axial loads, the effective height of the bridge pier, the moment of inertia, and mass. The functional application programming interface in the Keras Python library is utilized to develop a deep learning model considering all the above various input attributes. To have a robust and reliable prediction, the dataset for both the fast and slow cyclic tests is split into three mutually exclusive subsets of training, validation, and testing (unseen). The whole datasets include 17 RC bridge piers tested experimentally ten for fast and seven for slow cyclic tests. The results bring to light that the mean absolute error, as a loss function, is monotonically decreased to zero for both the training and validation datasets after 5000 epochs, and a high level of correlation is observed between the predicted and the experimentally measured values of the force time histories for all the datasets, more than 90%. It can be concluded that the maximum mean of the normalized error, obtained through Box-Whisker plot and Gaussian distribution of normalized error, associated with unseen data is about 10% and 3% for the fast and slow cyclic tests, respectively. In recapitulation, it brings to an end that the stacked Bi-CuDNNLSTM layer implemented in this study has a myriad of benefits in reducing the time and experimental costs for conducting new fast and slow cyclic tests in the future and results in a fast and accurate insight into hysteretic behavior of bridge piers.
Health promotion has come to the fore through new concept approach in consequence of the increase of chronic diseases. increase of medical cost and social trend of putting more emphasis on the individual responsibility for health. Studies of health promotion can be classified into two types: one is micro intervention method which is mainly focused on modifying individual life style and the other. macro intervention method in which they put another emphasis on the environment the individual is surrounded. in addition to modifying individual life style. This study belongs to the later. This study aims to develop nursing activities and program it for the purpose of community health promotion. The process of the study can be briefed as follows: to draw out nursing contents to intervene for community health promotion: to promote community health to develop nursing action indicators; to develop nursing action indicators for the development of main nursing activities. And those developed nursing activities are programmed systematically. The community health promotion program is composed of a hierarchical structure with nursing process that the nurses are supposed to apply to perform professional nursing. the level of nursing perform. the main items of nursing process. health promotion nursing indicators. health promotion nursing activities. The conclusion of this study according to objectives are as follows. First. community health promotion contents at individual and community level are remained revised and complemented and those at organizational level are developed. The developed main contents of community health promotion nursing are as follows. 1) Revised individual level nursing contents: 35 items. 2) Developed organizational level nursing contents: 24 items. 3) Revised community level nursing contents: 36 items. Second. for the development of the health promotion nursing action indicators. principles were set up and applied as follows. 1. Developed indicators should be provided with such qualities as comprehensiveness. diversity. developability, availability. practicability. 2. Developed indicators should be provided with functional abilities to measure the conditions and changes in any phenomena or state. inspect the development of the states. control the implementing program. evaluate the result of program and grasp what nurses should do. 3. Developed indicators should be provided with relevance and sequence. 4. Developed indicators should be undergo inspections from the expert. The developed community health promotion action indicators developed in this study. observing above mentioned principles. are total 330 indicators of 95 items. Third. when the main nursing activities were developed for each nursing action indicator. five priciples were set up in accordance with each nursing action indicators to decide main nursing activities. Main nursing activities developed observing those principles. are total 1273. Forth. for the programming of the developed nursing activities. three principles were set up. 1. The nursing activities are systematized in line with (nursing process) (nursing client) (key items of nursing process) (nursing action indicators for health promotion) (nursing activities). 2. The program is constructed in downward and hierarchical order. 3. The program is constructed not in relation to same level activities but in relation to high and low level activities. The process step of programming of developed main health promotion nursing activities are; Step 1. The Developed nursing action indicators are classified into nursing process. Step 2. The main nursing activities are allocated per each nursing action indicators. Step 3. The statement of main nursing activities are inspected. Step 4. The items of main nursing activities allocated by a certain nursing action indicators are sequenced. taking into consideration the elaborateness of activity. the sequency of activity. familiarity of activity. the difficulty of activity. the interest of activity. the frequency of activity. Step 5. The whole developed program should undergo comprehensive and critical inspections.
Journal of the Korea Academia-Industrial cooperation Society
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v.18
no.2
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pp.324-334
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2017
The simulators for a plant unit master control (UMC) developed by domestic or overseas researchers have been developed for operator-training purposes. UMC simulators normally constructed at the end of the plant construction, despite the UMC logics, should be simulated to pre-check many signal interfaces within the power generation systems. Because of the differences in construction schedule, it is difficult for logic designers or commissioning engineers to simulate the UMC logic during the design or commissioning stage. In this background, this paper proposes a simulation method that can be used easily by plant logic designers or operators in the MATLAB Simulink programming environment. The core of the UMC is realized with a unique simulation algorithm based on mathematical analysis and functional blocks combination. In addition, an integer-based configuration was proposed to realize the plant target value control for the equipment in the logic. With these simulation methods, functions, e.g., load distribution, high-low limitations, frequency compensation, etc. were simulated. The results showed that the plant UMC logic can be simulated in Simulink without a plant simulator. The various functions proposed in this paper can provide useful information about Simulink-based simulation design for plant logic designers or commissioning engineers during the power plant construction period.
Purpose - Due to highly elevated levels of competition, many companies today have to face the problem of decreasing profits even when their actual sales volume is increasing. This is a common phenomenon that is seen occurring among companies that focus heavily on quantitative growth rather than qualitative growth. These two aspects of growth should be well balanced for a company to create a sustainable business model. For supply chain management (SCM) planners, the optimized, quantified flow of resources used to be of major interest for decades. However, this trend is rapidly changing so that managers can put the appropriate balance between sales volume and sales quality, which can be evaluated from the profit margin. Profit optimization is a methodology for companies to use to achieve solutions focused more on profitability than sales volume. In this study, we attempt to provide executional insight for companies considering implementation of the profit optimization system to enhance their business profitability. Research design, data, and methodology - In this study, we present a comprehensive explanation of the subject of profit optimization, including the fundamental concepts, the most common profit optimization logic algorithm -linear programming -the business functional scope of the profit optimization system, major key success factors for implementing the profit optimization system at a business organization, and weekly level detailed business processes to actively manage effective system performance in achieving the goals of the system. Additionally, for the purpose of providing more realistic and practical information, we carefully investigate a profit optimization system implementation case study project fulfilled for company S. The project duration was about eight months, with four full-time system development consultants deployed for the period. To guarantee the project's success, the organization adopted a proven system implementation methodology, supply chain management (SCM) six-sigma. SCM six-sigma was originally developed by a group of talented consultants within Samsung SDS through focused efforts and investment in synthesizing SCM and six-sigma to improve and innovate their SCM operations across the entire Samsung Organization. Results - Profit optimization can enable a company to create sales and production plans focused on more profitable products and customers, resulting in sustainable growth. In this study, we explain the concept of profit optimization and prerequisites for successful implementation of the system. Furthermore, the efficient way of system security administration, one of the hottest topics today, is also addressed. Conclusion - This case study can benefit numerous companies that are eagerly searching for ways to break-through current profitability levels. We cannot guarantee that the decision to deploy the profit optimization system will bring success, but we can guarantee that with the help of our study, companies trying to implement profit optimization systems can minimize various possible risks across various system implementation phases. The actual system implementation case of the profit optimization project at company S introduced here can provide valuable lessons for both business organizations and research communities.
In the multimedia tele-medical system the medical informations are stored and managed in multimedia database. Also, multimedia DBMS is essential in order to manage large scale medical informations, and the remote access function is necessary for the distributed processing at all around the hospital. For the multimedia tele-medical information that is composed of image/picture, data, video, and audio, a high-speed telecommunication network is necessary that can provide separated connections for each medical information type with different QoS. The commercial DBMSs are based on the TCP/IP socket API(Application Programming Interface) that does not provide multiple QoS. Also, each commercial DBMS has its own API that is incompatible with other DBMS. In this paper, we propose a multimedia DBMS agent for the remote access of the multimedia database in the tele-medical system. The proposed multimedia DBMS agent is based on the ATM API that can provide high-speed data transfer capability and multiple QoS connections. Also, the proposed multimedia DBMS agent is independent of the commercial DBMS. We explain the functional architecture of the multimedia DBMS agent, implementation technology on the ATM network environment, and the result of performance analysis.
"The "Map Algebra", beeing recognized as a viable theoretical framework for GIS (Geographica Infonnation System), models map layers as "operands" which are the basic unit of geo-processing, and a variety of GIS commands as "operators." In this paper, we attempt at lifting some limitations of map algebras proposed in GIS literature. First, we model map layer as "function" such that we may employ the notion of meta operator (or, higher-order funtion) available in the functional programming paradigm. This approach provides map algebraic language with "programmability" needed in GIS user language. Second, we extend the semantics of, and improve on the sytactic structure of map algebraic language. Mer the data model and language associated with map algebra are formalized, we proceed to design and implement a prototype of map algebraic processor. The parser of the language in our prototype plays the role of transforming the native and heterogeneous user language of current GISs into a canonical map algebraic language. The prototype, named "MapSee" is a proof-of-concept system for the ideas we propsed in this paper. We believe that the uniform interface based on the map algebraic language will make promising infrastructure to support "Internet GIS." This is because the uniform but powerful interface through the Web clients allow access to both geo-data and geo-processing resources distributed over the network.to both geo-data and geo-processing resources distributed over the network.
Lee, Hak Geon;Yun, Chang Ho;Park, Jong Won;Lee, Yong Woo
Journal of Internet Computing and Services
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v.15
no.3
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pp.45-52
/
2014
The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.
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