• International journal of advanced smart convergence
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• 제4권1호
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• pp.31-34
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• 2015

Recently, the various types of data are began to increase. In order to manage the data efficiently, a variety of cloud services are being made. However, while providing a cloud service, the problem is the cost and waste a lot of human power to manage the data that is generated and managed by the server. To solve this problem, it is build the cloud environment using a single board computer with Raspberry pi. In this paper, we used Raspberry pi as a cloud server to provide services for the users. And we construct a Total Server to manage the generated data. It can separate the processing of data and the provision of services. We ensure the efficient operation by building a cloud environment with Raspberry pi and by managing the data which generated in cloud environment with the total server.

• Journal of the Korea Society of Computer and Information
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• 제11권2호
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• pp.145-151
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• 2006

In conjunction with the rapid progress of IT(information technology) an increasing amount of data are being generated. The amount of new data is so big and the type of new data generated from clients or sensor devices needed to be in ubiquitous environment is so various that it is hard to manage and control them. Especially data to be occurred in ubiquitous environment are generated through PDA(personal digital assistant) smart phone, mobile device or sensor units etc. Therefore, to manage and control them generated from ubiquitous devices for decision making, we can use data warehouse as an integrated storage. A data warehouse integrates and aggregates data of several different DBMS into one DBMS. Also the updated data from source data have to be effectively propagated to the data warehouse. Therefore, in this paper, we proposed a mode) for an exact and efficient data management methodology in new IT paradigm environment, ubiquitous computing environment, to apply updated data on the warehouse to make decision. We also show brief result compared to conventional methodology.

• Journal of Information Technology Applications and Management
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• 제30권6호
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• pp.143-155
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• 2023

Procedural generation methods based on physical-based materials generate data by algorithms rather than manual through combinations with artist-generated assets based on computer-generated randomness algorithms. For this reason, the procedural generation method is mainly used to produce textures of 3D models in the field of computer graphics because it is easy to obtain the desired quality with little data. This study is a study on physical-based materials and procedural generation methods based on them. Physical-based materials are divided into Metallic/Roughness workflows and Specific/Glossiness workflows. These two methods produce the same results, which are more accurate based on the law of conservation of energy. The procedural generation method allows a natural texture to be obtained very quickly by texturing through a combination of a computer-generated random algorithm and an artist-generated asset based on various maps.

• Water Engineering Research
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• 제2권4호
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• pp.209-218
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• 2001

Generation of evaporation data generally assists in planning, operation, and management of reservoirs and other water works. Annual and monthly evaporation series were generated for King Fahad Dam Lake in Bishah, Saudi Arabia. Data was gathered for period of 22 years. Tests of homogeneity and normality were conducted and results showed that data was homogeneous and normally distributed. For generating annual series, an Autoregressive first order model AR(1) was used and for monthly evaporation series method of fragments was used. Fifty replicates for annual series, and fifty replicates for each month series, each with 22 values length, were generated. Performance of the models was evaluated by comparing the statistical parameters of the generated series with those of the historical data. Annual and monthly models were found to be satisfactory in preserving the statistical parameters of the historical series. About 89% of the tested values of the considered parameters were within the assigned confidence limits

• Communications for Statistical Applications and Methods
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• 제23권6호
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• pp.517-529
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• 2016

This study compares the inverse transform and the composition methods for generating data from the Lindley distribution. The expression for the inverse of the distribution function for the Lindley distribution does not exist in closed form. Hence, authors of many empirical studies on the Lindley distribution used methods for generating Lindley variates other than the inverse transform. We generated data from the Lindley distribution using the inverse transform approach by obtaining the Lindley variates numerically; we also generated data from this distribution using the composition approach. Following the generation of the Lindley variates using these two methods, we compare some statistical properties of the estimates of the Lindley model parameters based on the generated data. We conclude that the two methods produce similar results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제32권3호
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• pp.217-223
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• 2014

With precise sensor position, attitude element, and imaging resolution, a simulated geospatial image can be generated. In this study, a satellite image is simulated using SPOT ortho-image and global elevation data, and the geometric similarity between original and simulated images is analyzed. Using a SPOT panchromatic image and high-density elevation data from a 1/5K digital topographic map data an ortho-image with 10-meter resolution was produced. The simulated image was then generated by exterior orientation parameters and global elevation data (SRTM1, GDEM2). Experimental results showed that (1) the agreement of the image simulation between pixel location from the SRTM1/GDEM2 and high-resolution elevation data is above 99% within one pixel; (2) SRTM1 is closer than GDEM2 to high-resolution elevation data; (3) the location of error occurrence is caused by the elevation difference of topographical objects between high-density elevation data generated from the Digital Terrain Model (DTM) and Digital Surface Model (DSM)-based global elevation data. Error occurrences were typically found at river boundaries, in urban areas, and in forests. In conclusion, this study showed that global elevation data are of practical use in generating simulated images with 10-meter resolution.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.1035-1036
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• 2006

We analyzed the performance of hierarchical cellular system with multi traffic(voice traffic, data traffic). We executed the computer simulation by the various ratio of traffic generation(voice traffic, data traffic). We generated data traffic at microcell. The more voice traffic generated, the higher the block probability of data traffic became at macrocell.

• Journal of Information Processing Systems
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• 제7권2호
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• pp.363-384
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• 2011

As the complexity of software is increasing, generating an effective test data has become a necessity. This necessity has increased the demand for techniques that can generate test data effectively. This paper proposes a test data generation technique based on adequacy based testing criteria. Adequacy based testing criteria uses the concept of mutation analysis to check the adequacy of test data. In general, mutation analysis is applied after the test data is generated. But, in this work, we propose a technique that applies mutation analysis at the time of test data generation only, rather than applying it after the test data has been generated. This saves significant amount of time (required to generate adequate test cases) as compared to the latter case as the total time in the latter case is the sum of the time to generate test data and the time to apply mutation analysis to the generated test data. We also use genetic algorithms that explore the complete domain of the program to provide near-global optimum solution. In this paper, we first define and explain the proposed technique. Then we validate the proposed technique using ten real time programs. The proposed technique is compared with path testing technique (that use reliability based testing criteria) for these ten programs. The results show that the adequacy based proposed technique is better than the reliability based path testing technique and there is a significant reduce in number of generated test cases and time taken to generate test cases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.324-325
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• 2016

The sensor network-based service collects data by using the sensor, the data is aware of the situation via the analysis, and the service provider provides a service suitable for the user via the context-awareness. However, this data is generated, it is difficult to match the metadata and standard units. The data integration is required to use the data generated by the different specifications of the sensor efficiently. Accordingly, in this paper we propose a method using an ontology as a method to integrate the data generated by the existing sensors and the new sensor. The ontology is mapping to the standard item and sensors, also include a type and structural difference. The mapping is comprised of two:data mapping, and metadata mapping. There are standard items that are created in this way, type of data exchange between services. This can solve the heterogeneous problem generated by sensors.

• Journal of Internet of Things and Convergence
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• 제8권5호
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• pp.127-132
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• 2022

As the IoT technology is more developed, it is more important for the accuracy of IoT data. Since the IoT data supports a different formats and protocols, it is often happened that the IoT system is failed or the incorrect data is generated with the unreliable IoT devices(sensor, actuator). Because the abnormality of IoT device or the user situation is not detected correctly, this problem makes the user to be unsatisfied with the IoT system. This study proposes the decision methodology of IoT data consistency whether the IoT data is generated in normal range or not by using the mathematical functions('gradient descent function' and 'linear regression function'). It may be concluded that the gradient function method is suitable for the IoT data which the 'increasing velocity' is related with the next generated pattern(eg. sensor devices), the linear regression function method is suitable for the IoT data which the 'the difference from linear regression function' is related with the next generated pattern in case the data has a linear pattern(eg. water meter, electric meter).