• International Journal of Computer Science & Network Security
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• v.24 no.10
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• pp.43-52
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• 2024

A medium scale Urdu speakers' and English speakers' database with multiple accents and dialects has been developed to use in Urdu Speaker Verification Systems, English Speaker Verification Systems, accents and dialect verification systems. Urdu is the national language of Pakistan and English is the official language. Majority of the people are non-native Urdu speakers and non-native English in all regions of Pakistan in general and Gilgit-Baltistan region in particular. In order to design Urdu and English speaker verification systems for security applications in general and telephone banking in particular, two databases has been designed one for foreign accent of Urdu and another for foreign accent of English language. For the design of databases, voice data is collected from 180 speakers from GB region of Pakistan who could speak Urdu as well as English. The speakers include both genders (males and females) with different age groups ranging from 18 to 69 years. Finally, using a subset of the data, Multilayer Perceptron based speaker verification system has been designed. The designed system achieved overall accuracy rate of 83.4091% for English dataset and 80.0454% for Urdu dataset. It shows slight differences (4.0% with English and 7.4% with Urdu) in recognition accuracy if compared with the recently proposed multilayer perceptron (MLP) based SIS achieved 87.5% recognition accuracy

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.617-623
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• 2018

This study focuses on detection of malicious code through AndroidManifest permissoion feature extracted based on Android static analysis. Features are built on the permissions of AndroidManifest, which can save resources and time for analysis. Malicious app detection model consisted of SVM (support vector machine), NB (Naive Bayes), Gradient Boosting Classifier (GBC) and Logistic Regression model which learned 1,500 normal apps and 500 malicious apps and 98% detection rate. In addition, malicious app family identification is implemented by multi-classifiers model using algorithm SVM, GPC (Gaussian Process Classifier) and GBC (Gradient Boosting Classifier). The learned family identification machine learning model identified 92% of malicious app families.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.545-554
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• 2006

RFID could be applied in the various fields such as distribution beside, circulation, traffic and environment on information communication outside. So this can speak as point of ubiquitous computing's next generation technology. However, it is discussed problem of RFID security recently, so we must prepare thoroughly about RFID security for secure information. In this paper, we proposed a method which could protect private information and ensure RFID's identification effectively storing face feature information on RFID tag. Our method which is improved linear discriminant analysis has reduced dimension of feature information which has large size of data. Therefore, we can sore face feature information in small memory field of RFID tag. Our propose d algorithm has shown 92% recognition rate in experimental results and can be applied to entrance control management system, digital identification card and others.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.521-526
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• 2015

Research on how to use the biological characteristics of human to confirm the identity of the individual is being actively conducted. Electrocardiogram(: ECG) based biometric system is difficult to counterfeit and does not cause skin irritation on the subject. It can be easily combined with conventional biometrics such as fingerprint and face recognition to give multimodal biometric systems. In this thesis, biometric identification method analysing ECG waveform characteristics from Discrete Wavelet Transform(DWT) coefficients is suggested. Feature selection is performed on the 9 coefficients of DWT using the correlation analysis. The verification is achieved by using the error back propagation neural networks. Using the proposed approach on 24 subjects of MIT-BIH QT Database, 98.88% verification rate has been obtained.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.91-95
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• 2005

In the multidimensional protein identification technology of high-throughput proteomics, we use one-dimensional gel electrophoresis and after the separation by two-dimensional liquid chromatography, the sample is analyzed by tandem mass spectrometry. In this study, we have analyzed the Pseudomonas Putida KT2440 protein. From the protein identification, the protein database was combined with its reversed sequence database. From the peptide selection whose error rate is less than 1%, the SEQUEST database search for the tandem mass spectral data identified 2,045 proteins. For each protein, we compared the molecular weight calibrated from 1D-gel band position with the theoretical molecular weight computed from the amino acid sequence, by defining a variable MW$_{corr}$ Since the bacterial proteome is simpler than human proteome considering the complexity and modifications, the proteome analysis result for the Pseudomonas Putida KT2440 could suggest a guideline to build the protocol to analyze human proteome data.

• Journal of Pharmaceutical Investigation
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• v.24 no.4
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• pp.233-243
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• 1994

Precipitation was formed during the preparation of decoction from a mixture of Scutellariae Radix and Coptidis Rhizoma or Phellodendri Cortex according to the prescription of Hwang-ryean-hae-dog-tang. Baicalin and berberine were identified in coprecipitated product and these components were the active ingredients of two herbal medicine. The coprecipitated product was very slightly soluble in water and sparingly soluble in ethanol. The stoichiometric ratio of baicalin and berberine was found to be 1:1. The lipid-water partition coefficients of coprecipitated product were increased more than baicalin and berberine in chloroform, but were decreased in other organic solvents. The content of baicalin and berberine in coprecipitated product, determined by HPLC, were 23.08% and 26.75%, but the content of active ingredients in supernatant were 0.66% and 0.26%, respectively. The dissolution profile of baicalin of coprecipitated product was increased more than extract of Scutellariae Radix in artificial gastric juice, but was decreased in artificial intestinal juice. The dissolution rate of berberine of coprecipitated product was lower than extract of Coptidis Rhizoma in artificial gastric juice and intestinal juice commonly.

• Korean Journal of Pharmacognosy
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• v.15 no.3
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• pp.139-146
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• 1984

High performance liquid chromatographic separation is described for the analysis of bile acids after hydrolysis in seven commercial crude bile drugs and ox and pig galls. They are simultaneously separated with HPLC mobile phase of acetonitrile/0.5% ammonium carbonate (pH 6.7) (25.5 : 74.5) at a flow rate $(1.0{\rightarrow}1.5ml/min.)$ and differential refractometer. The linearity of calibration curve and recovery test are good by using the method. The analysis of major bile acids in seven commercial crude bile drugs using the described method is presented. Sample no. 1 of them is similar to separation pattern of ox gall. Sample no. 6 of them is supposed to be genuine bear gall on the basis of identification of ursodeoxycholic acid. Sample $no.\;2{\sim}5$ and 7 of them are supposed to be pig gall on the basis of identification of hyodeoxycholic acid which is a characteristic component of pig gall.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1342-1350
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• 1999

In this paper, we have developed and analyzed the 2.45GHz microwave RFID system. Which is composed tag and interrogator using custom IC, and we have made the software driving the hardware for the bidirectional data transmission method. Using 3.6V power supply was used, the optimal identification range in the information transmission of the designed microwave RFID system operating at 9,600bps was l0m. In the control circuit of the tag, the low current consumption of 15$mutextrm{A}$ and the tag data transmission rate of 90% when the moving velocity was 80km/h.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.101-107
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• 2008

We introduce an optimization of fuzzy set-fuzzy systems based on IG (Information Granules). The proposed fuzzy model implements system structure and parameter identification by means of IG and GAs. The concept of information granulation was coped with to enhance the abilities of structural optimization of the fuzzy model. Granulation of information realized with C-Means clustering helps determine the initial parameters of the fuzzy model such as the initial apexes of the membership functions in the premise part and the initial values of polynomial functions in the consequence part of the fuzzy rules. The initial parameters are adjusted effectively with the help of the GAs and the standard least square method. To optimally identify the structure and the parameters of the fuzzy model we exploit GAs with successive tuning method to simultaneously search the structure and the parameters within one individual. We also consider the variant generation-based evolution to adjust the rate of identification of the structure and the parameters in successive tuning method. The proposed model is evaluated with the performance of the conventional fuzzy model.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.499-507
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• 2006

Recently human gait has been considered as a useful biometric supporting high performance human identification systems. This paper proposes a view-based pedestrian identification method using the dynamic silhouettes of a human body modeled with the Hidden Markov Model(HMM). Two types of gait models have been developed both with an endless cycle architecture: one is a discrete HMM method using a self-organizing map-based VQ codebook and the other is a continuous HMM method using feature vectors transformed into a PCA space. Experimental results showed a consistent performance trend over a range of model parameters and the recognition rate up to 88.1%. Compared with other methods, the proposed models and techniques are believed to have a sufficient potential for a successful application to gait recognition.