Search results for: Sujeung Cheong

Authors: Minsoo Lee, Yearn Jeong Kim, Yun-mi Kim, Sujeung Cheong, Sookyung Song

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Bio-chips are used for experiments on genes and contain various information such as genes, samples and so on. The two-dimensional bio-chips, in which one axis represent genes and the other represent samples, are widely being used these days. Instead of experimenting with real genes which cost lots of money and much time to get the results, bio-chips are being used for biological experiments. And extracting data from the bio-chips with high accuracy and finding out the patterns or useful information from such data is very important. Bio-chip analysis systems extract data from various kinds of bio-chips and mine the data in order to get useful information. One of the commonly used methods to mine the data is classification. The algorithm that is used to classify the data can be various depending on the data types or number characteristics and so on. Considering that bio-chip data is extremely large, an algorithm that imitates the ecosystem such as the ant algorithm is suitable to use as an algorithm for classification. This paper focuses on finding the classification rules from the bio-chip data using the Ant Colony algorithm which imitates the ecosystem. The developed system takes in consideration the accuracy of the discovered rules when it applies it to the bio-chip data in order to predict the classes.

Keywords: Ant Colony System, DNA chip data, Classification.

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Authors: Chin Wen Cheong

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This study employs a bivariate asymmetric GARCH model to reveal the hidden dynamics price changes and volatility among the emerging markets of Thailand and Malaysian after the Asian financial crisis from January 2001 to December 2008. Our results indicated that the equity markets are sharing the common information (shock) that transmitted among each others. These empirical findings are used to demonstrate the importance of shock and volatility dynamic transmissions in the cross-market hedging and market risk.

Keywords: multivariate ARCH, structural change, value at risk.

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Authors: Minho Ha, SeungHeo, Cheolung Cheong, Park K. Y.

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In this paper, a new cooling system using a nacelle duct is proposed for the mechanical room in the household refrigerator. The conventional mechanical room consists of a condenser, a compressor and an axial fan. The axial fan is mainly responsible for cooling the condenser and the compressor. The new cooling system is developed by replacing the axial fan with the nacelle duct including the small centrifugal fan. The parametric study is carried out to find the optimum designs of the nacelle duct in terms of performance and efficiency. Through this study, it is revealed that the new system can reduce the space, electrical power and noise compared with the conventional system

Keywords: Centrifugal Fan, Cooling Fan, Nacelle Duct, Refrigerator

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Authors: Nhat Khoa Tran, Yee Cheong Lam, Chee Yoon Yue, Ming Jen Tan

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Metallic micro parts are playing an important role in micro-fabrication industry. Recently, we have demonstrated a new deformation mechanism for micro-formability of polycrystalline materials. Different depressed micro-features smaller than the grain size have been successfully fabricated on 6061 aluminum alloy (AA6061) substrates with good fidelity. To further verify this proposed deformation mechanism that grain size is not a limiting factor, we demonstrate here that in addition of depressed features, protruded micro-features on a polycrystalline substrate can similarly be fabricated.

Keywords: Deformation mechanism, grain size, microfabrication, polycrystalline materials.

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Authors: Jing Hang Choo, Soon Nyean Cheong, Yee Lien Lee, Sze Hou Teh

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The advancement of smartphones, wireless networking and Near Field Communication (NFC) technology have opened up a new approach to indoor navigation. Although NFC technology has been used to support electronic commerce, access control, and ticketing, there is a lack of research work on building NFC-based indoor navigation system for smartphone users. This paper presents an indoor interactive navigation system (named I2Navi) based on NFC technology for users to navigate within a building with ease using their smartphones. The I2Navi system has been implemented at the Faculty of Engineering (FOE), Multimedia University (MMU) to enable students, parents, visitors who own NFC-enabled Android smartphones to navigate themselves within the faculty. An evaluation is carried out and the results show positive response to the proposed indoor navigation system using NFC and smartphone technologies.

Keywords: Near Field Communication, indoor navigation system, smartphones.

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Authors: Hang-cheong Wong, Pak-kin Wong, Chi-man Vong, Zhengchao Xie, Shaojia Huang

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Automotive engine air-ratio plays an important role of emissions and fuel consumption reduction while maintains satisfactory engine power among all of the engine control variables. In order to effectively control the air-ratio, this paper presents a model predictive fuzzy control algorithm based on online least-squares support vector machines prediction model and fuzzy logic optimizer. The proposed control algorithm was also implemented on a real car for testing and the results are highly satisfactory. Experimental results show that the proposed control algorithm can regulate the engine air-ratio to the stoichiometric value, 1.0, under external disturbance with less than 5% tolerance.

Keywords: Air-ratio, Fuzzy logic, online least-squares support vector machine, model predictive control.

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Authors: Kah-Hyong Chang, Xin Liu, Jia Hao Cheong, Saisundar Sankaranarayanan, Dexing Pang, Hongzhao Zheng

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A digital baseband Application-Specific Integrated Circuit (ASIC) (yclic Redundancy Checkis developed for a microchip transponder to transmit signals and temperature levels from biomedical monitoring devices. The transmission protocol is adapted from the ISO/IEC 11784/85 standard. The module has a decimation filter that employs only a single adder-subtractor in its datapath. The filtered output is coded with cyclic redundancy check and transmitted through backscattering Load Shift Keying (LSK) modulation to a reader. Fabricated using the 0.18-μm CMOS technology, the module occupies 0.116 mm² in chip area (digital baseband: 0.060 mm², decimation filter: 0.056 mm²), and consumes a total of less than 0.9 μW of power (digital baseband: 0.75 μW, decimation filter: 0.14 μW).

Keywords: Biomedical sensor, decimation filter, Radio Frequency Integrated Circuit (RFIC) baseband, temperature sensor.

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Authors: Minsoo Lee, Yoon-kyung Lee, Hyejung Yoon, Soo-kyung Song, Sujeong Cheong

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Data Warehousing tools have become very popular and currently many of them have moved to Web-based user interfaces to make it easier to access and use the tools. The next step is to enable these tools to be used within a portal framework. The portal framework consists of pages having several small windows that contain individual data warehouse query results. There are several issues that need to be considered when designing the architecture for a portal enabled data warehouse query tool. Some issues need special techniques that can overcome the limitations that are imposed by the nature of data warehouse queries. Issues such as single sign-on, query result caching and sharing, customization, scheduling and authorization need to be considered. This paper discusses such issues and suggests an architecture to support data warehouse queries within Web portal frameworks.

Keywords: Data Warehousing tools, data warehousing queries, web portal frameworks.

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Authors: Kam-moon Liu, Kwok-chi Chim, Kwok-wai Chung, Daniel Wing-cheong Ho

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Students often adopt routine practicing as learning strategy for mathematics. The reason is they are often bound and trained to solving conventional-typed questions in Mathematics in high school. This will be problematic if students further consolidate this practice in university. Therefore, the Department of Mathematics emphasized and integrated the Discovery-enriched approach in the undergraduate curriculum. This paper presents the details of implementing the Discovery-enriched Curriculum by providing adequate platform for project-learning, expertise for guidance and internship opportunities for students majoring in Mathematics. The Department also provided project-learning opportunities to mathematics courses targeted for students majoring in other science or engineering disciplines. The outcome is promising: the research ability and problem solving skills of students are enhanced.

Keywords: Discovery-enriched curriculum, higher education, mathematics education, project learning.

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Authors: Dany Ng Cheong Vee, Preethee Nunkoo Gonpot, Noor-Ul-Hacq Sookia

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In this paper, we consider the application of Extreme Value Theory as a risk measurement tool. The Value at Risk, for a set of indices, from six Stock Exchanges of Frontier markets is calculated using the Peaks over Threshold method and the performance of the model index-wise is evaluated using coverage tests and loss functions. Our results show that “fattailedness” alone of the data is not enough to justify the use of EVT as a VaR approach. The structure of the returns dynamics is also a determining factor. This approach works fine in markets which have had extremes occurring in the past thus making the model capable of coping with extremes coming up (Colombo, Tunisia and Zagreb Stock Exchanges). On the other hand, we find that indices with lower past than present volatility fail to adequately deal with future extremes (Mauritius and Kazakhstan). We also conclude that using EVT alone produces quite static VaR figures not reflecting the actual dynamics of the data.

Keywords: Extreme Value theory, Financial Crisis 2008, Frontier Markets, Value at Risk.

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Authors: Sae-Rom Pak, Seung Hwan Park, Jeong Ho Cho, Daewoong An, Cheong-Sool Park, Jun Seok Kim, Jun-Geol Baek

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It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.

Keywords: Yield Prediction, Semiconductor Test Process, Support Vector Machine, Under Sampling

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Authors: Lei Yao, Jia Hao Cheong, Rui-Feng Xue, Minkyu Je

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A closed-loop controlled wireless power transmission circuit block for implantable biomedical applications is described in this paper. The circuit consists of one front-end rectifier, power management sub-block including bandgap reference and low drop-out regulators (LDOs) as well as transmission power detection / feedback circuits. Simulation result shows that the front-end rectifier achieves 80% power efficiency with 750-mV single-end peak-to-peak input voltage and 1.28-V output voltage under load current of 4 mA. The power management block can supply 1.8mA average load current under 1V consuming only 12μW power, which is equivalent to 99.3% power efficiency. The wireless power transmission block described in this paper achieves a maximum power efficiency of 80%. The wireless power transmission circuit block is designed and implemented using UMC 65-nm CMOS/RF process. It occupies 1 mm × 1.2 mm silicon area.

Keywords: Implantable biomedical devices, wireless power transfer, LDO, rectifier, closed-loop power control

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Authors: Jun Seok Kim, Cheong-Sool Park, Jun-Geol Baek, Sung-Shick Kim

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Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.

Keywords: Control chart pattern recognition, Multi-resolution wavelet analysis, Bi-directional Kohonen network, Back-propagation network, Feature extraction.

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Authors: Tru C. Le, France Cheong

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Although the Vietnamese catfish farming has grown at very high rates in recent years, the industry has also faced many problems affecting its sustainability. This paper studies the perceptions of catfish farmers regarding risk and risk management strategies in their production activities. Specifically, the study aims to measure the consequences, likelihoods, and levels of risks as well as the efficacy of risk management in Vietnamese catfish farming. Data for the study were collected through a sample of 261 catfish farmers in the Mekong Delta, Vietnam using a questionnaire survey in 2008. Results show that, in general, price and production risks were perceived as the most important risks. Farm management and technical measures were perceived more effective than other kinds of risk management strategies in risk reduction. Although price risks were rated as important risks, price risk management strategies were not perceived as important measures for risk mitigation. The results of the study are discussed to provide implications for various industry stakeholders, including policy makers, processors, advisors, and developers of new risk management strategies.

Keywords: Aquaculture, catfish farming, sources of risk, riskmanagement, risk strategies, risk mitigation.

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Authors: Haridas Kuruveettil, Dongning Zhao, Cheong Jia Hao, Minkyu Je

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We present the design of Analog front end (AFE) low noise pre-amplifier implemented in a high voltage 0.18-µm CMOS technology for  a three dimensional ultrasound  bio microscope (3D UBM) application. The fabricated chip has 4X16 pre-amplifiers implemented to interface   a 2-D array of    high frequency capacitive micro-machined ultrasound transducers (CMUT). Core AFE cell consists of a high-voltage pulser in the transmit path, and a low-noise transimpedance amplifier in the receive path. Proposed system offers a high image resolution by the use of high frequency CMUTs with associated high performance imaging electronics integrated together.  Performance requirements and the design methods of the high bandwidth transimpedance amplifier are described in the paper. A single cell of transimpedance (TIA) amplifier and the bias circuit occupies a silicon area of 250X380 µm² and the full chip occupies a total silicon area of 10x6.8 mm².

Keywords: Ultrasound, analog front end, medical imaging, beam forming, biomicroscope, transimpedance gain.

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Authors: Youngji Yoo, Cheong-Sool Park, Jun Seok Kim, Young-Hak Lee, Sung-Shick Kim, Jun-Geol Baek

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In the semiconductor manufacturing process, large amounts of data are collected from various sensors of multiple facilities. The collected data from sensors have several different characteristics due to variables such as types of products, former processes and recipes. In general, Statistical Quality Control (SQC) methods assume the normality of the data to detect out-of-control states of processes. Although the collected data have different characteristics, using the data as inputs of SQC will increase variations of data, require wide control limits, and decrease performance to detect outof- control. Therefore, it is necessary to separate similar data groups from mixed data for more accurate process control. In the paper, we propose a regression tree using split algorithm based on Pearson distribution to handle non-normal distribution in parametric method. The regression tree finds similar properties of data from different variables. The experiments using real semiconductor manufacturing process data show improved performance in fault detecting ability.

Keywords: Semiconductor, non-normal mixed process data, clustering, Statistical Quality Control (SQC), regression tree, Pearson distribution system.

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