• Journal of Power System Engineering
• /
• v.7 no.2
• /
• pp.29-35
• /
• 2003

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a classification method of diagnosing the small reciprocating compressor for refrigerators using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them ate compared with each other. This paper is focused on the development of an advanced signal classifier to automatize the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2000.11a
• /
• pp.796-801
• /
• 2000

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a signal classification method for diagnosing the rotating machinery using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them are compared with each other. This paper is focused on the development of an advanced signal classifier to automatise the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• Journal of Korean Elementary Science Education
• /
• v.29 no.4
• /
• pp.441-450
• /
• 2010

The purpose of this study was to evaluate the level of elementary gifted students' argumentation and examine the special features of argumentation founded in scientific inquiry. 28 students were selected in the special education center for the gifted in K National University. They were organized 8 groups of 3~4 students and engaged in scientific inquiry activity. The researcher wasn't involved in students' inquiry activity and argumentation except for the guiding and introducing their activity. In the first session, each group carried out the experiment 'Putting a heated can in the water' and then, the students discussed to probe their experimental results and build their explanation. In the second session, each group presented their experiment results and evidence from their experiment justifying their claims, and had questions from other groups. The protocol data during 8 groups' argumentations were analyzed using 'Rubric for Scientific Argumentation Assessment' (Yang et al., 2009) in three domains- the form, content and attitude. As a result, in form domain, almost groups were rated 2 points due to their argument without rebuttal on the subcategory of 'composition', but they got a good grade above 3 points in subcategory such as 'claim', 'ground', and 'conclusion'. In content domain, almost groups got points above 3 points. In attitude domain, there were some striking contrast between each groups. Six groups got good score more than 4 points on the subcategory of openness, but two groups, they alleged and got score below 3 point. While the 6 groups of all got 4 points in the aspect of participation, 3 groups got 3 points lower than because they only just asserted and not interact with other groups. Throughout the argumentation, two features were found that; as time goes by, arguments were refined; Students tended to use their prior to knowledge rather than evidence such as experimental data in making claims and conclusions.

• The Transactions of the Korea Information Processing Society
• /
• v.2 no.5
• /
• pp.691-700
• /
• 1995

Most fractal image codings using fractal concept require long encoding time because a large amount of computation is needed to find an optimal affine transformation point. Such a problem can be solved by designing a block classifier fitted to characteristics of image blocks. In general, it is possible to predict more precise and various types of blocks in frequency domain than in spatial domain. In this paper, we propose a block classifier to predict the block type using characteristics of DCT(Discrete Cosine Transform). This classifier has merits to enhance the quality of decoded images as well as to reduce the encoding time meeting fractal features. AC coefficient values in frequency domain make it possible to predict various types of blocks. As the results, the number of comparisons between a range block and the correspoding domain blocks to reach an optimal affine transformation point can be reduced. Specially, signs of DCT coefficients help to find the optimal affine transformation point with only two isometric transformations by eliminating unnecessary isometric transformations among eight isometric transformations used in traditional fractal codings.

• Computers and Concrete
• /
• v.16 no.4
• /
• pp.503-529
• /
• 2015

Traditionally, multi-story buildings are designed to provide stiffer structural support to withstand lateral earthquake loading. Introducing flexible elements at the base of a structure and providing sufficient damping is an alternative way to mitigate seismic hazards. These features can be achieved with a device known as an isolator. This paper covers the design of base isolators for multi-story buildings in medium-risk seismicity regions and evaluates the structural responses of such isolators. The well-known tower building for police personnel built in Dhaka, Bangladesh by the Public Works Department (PWD) has been used as a case study to justify the viability of incorporating base isolators. The objective of this research was to establish a simplified model of the building that can be effectively used for dynamic analysis, to evaluate the structural status, and to suggest an alternative option to handle the lateral seismic load. A finite element model was incorporated to understand the structural responses. Rubber-steel bearing (RSB) isolators such as Lead rubber bearing (LRB) and high damping rubber bearing (HDRB) were used in the model to insert an isolator link element in the structural base. The nonlinearities of rubber-steel bearings were considered in detail. Linear static, linear dynamic, and nonlinear dynamic analyses were performed for both fixed-based (FB) and base isolated (BI) buildings considering the earthquake accelerograms, histories, and response spectra of the geological sites. Both the time-domain and frequency-domain approaches were used for dynamic solutions. The results indicated that for existing multi-story buildings, RSB diminishes the muscular amount of structural response compared to conventional non-isolated structures. The device also allows for higher horizontal displacement and greater structural flexibility. The suggested isolation technique is able to mitigate the structural hazard under even strong earthquake vulnerability.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.6 no.7
• /
• pp.1126-1132
• /
• 2002

In this paper, we propose a new scheme of motion tracking based on fuzzy inference (Fl) and wavelet transform (WT) from image sequences. First, we present a WT to segment a feature extraction of dynamic image . The coefficient matrix for 2-level DWT tent to be clustered around the location of Important features in the images, such as edge discontinuities, peaks, and corners. But these features are time varying owing to the environment conditions. Second, to reduce the spatio-temperal error, We develop a fuzzy inference algorithm. Some experiments are performed 0 testify the validity and applicability of the proposed system As a result, proposed method is relatively simple compared with the traditional space domain method. It is also well suited for motion tracking under the conditions of variation of illumination.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.2
• /
• pp.177-188
• /
• 2012

GIS provides the various analyzing and displaying using diverse spatial data have supported the powerful functionality and friendly user-interface. But, early GIS software is developed as package tool, it have many difficulties with reducing the cost of developing GPS application and satisfying the various user requirements. At present, the developed GPS applications across multiple domains, despite the common features are built separately for each domain in terms of software engineering development followed out waste of time and money expenditure. However, common features between GPS applications, if deployed as a component assembly and reuse components in terms of enabling the two kinds of component-based development can bring out the beneficial results. In this paper, we described the Analysis and design of GPS ApplicationsS based on Component. Each GPS component is composed of many objects accomplish the atomic service processing and cooperate with each other. And, GPS components meets the qualifications of thc low cost of developing GPS application because of the reusability and re-composition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.11a
• /
• pp.217-221
• /
• 2002

In this paper, we propose a new scheme of motion tracking based on fuzzy inference (FI)and wavelet transform (WT) from image sequences. First, we present a WT to segment a feature extraction of dynamic image . The coefficient matrix for 2-level DWT tent to be clustered around the location of important features in the images, such as edge discontinuities, peaks, and corners. But these features are time varying owing to the environment conditions. Second, to reduce the spatio-temporal error, We develop a fuzzy inference algorithm. Some experiments are peformed to testify the validity and applicability of the proposed system. As a result, proposed method is relatively simple compared with the traditional space domain method. It is also well suited for motion tracking under the conditions of variation of illumination.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.10 no.3
• /
• pp.165-175
• /
• 2010

This paper presents a fine-grain supply-voltage-control scheme for low-power FPGAs. The proposed supply-voltage-control scheme detects the critical path in real time with small overheads by exploiting features of asynchronous architectures. In an FPGA based on the proposed supply-voltage-control scheme, logic blocks on the sub-critical path are autonomously switched to a lower supply voltage to reduce the power consumption without system performance degradation. Moreover, in order to reduce the overheads of level shifters used at the power domain interface, a look-up-table without level shifters is employed. Because of the small overheads of the proposed supply-voltage-control scheme and the power domain interface, the granularity size of the power domain in the proposed FPGA is as fine as a single four-input logic block. The proposed FPGA is fabricated using the e-Shuttle 65 nm CMOS process. Correct operation of the proposed FPGA on the test chip is confirmed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2013.10a
• /
• pp.338-345
• /
• 2013

Induction motors play an increasing importance in industrial manufacturing. Therefore, the state monitoring systems also have been considering as the key in dealing with their negative effect by absorbing faulty symptoms in motors. There are numerous proposed systems in literature, in which, several kinds of signals are utilized as the input. To solve the multiple faults problem of induction motors, like the proposed system, the vibration signals is good candidate. In this study, a new signal processing scheme was utilized, which transforms the time domain vibration signal into the spatial domain as an image. Then the spatial features of converted image then have been extracted by applying the dominant neighbourhood structure (DNS) algorithm. In addition, these feature vectors were evaluated to obtain the fruitful dimensions, which support to discriminate between states of motors. Because of reliability, the conventional one-against-all (OAA) multi-class support vector machines (MCSVM) have been utilized in the proposed system as classifier module. Even though examined in severity levels of signal-to-noise ratio (SNR), up to 15dB, the proposed system still reliable in term of two criteria: true positive (TF) and false positive (FP). Furthermore, it also offers better performance than five state-of-the-art systems.