• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.226-231
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• 2013

In The matching algorithm for automatic packaging of drugs is essential to determine whether the canister can exactly refill the suitable medicine. In this paper, we propose a hierarchical neural network with the upper and lower layers which can perform real-time processing and classification of many types of medicine bottles to prevent accidental medicine disaster. A few number of low-dimensional feature vector are extracted from the label images presenting medicine-bottle information. By using the extracted feature vectors, the lower layer of MLP(Multi-layer Perceptron) neural networks is learned. Then, the output of the learned middle layer of the MLP is used as the input to the upper layer of the MLP learning. The proposed hierarchical neural network shows good classification performance and real- time operation in the test of up to 30 degrees rotated to the left and right images of 100 different medicine bottles.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.409-416
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• 2013

Attention is one of important cognitive functions in human affecting on the selectional concentration of relevant events and ignorance of irrelevant events. The discrimination of attentional and inattentional status is the first step to manage human's attentional capability using computer assisted device. In this paper, we newly combine the non-linear recurrence pattern analysis and spectrum analysis to effectively extract features(total number of 13) from the electroencephalographic signal used in the input to classifiers. The performance of diverse types of attention-inattention classifiers, including supporting vector machine, back-propagation algorithm, linear discrimination, gradient decent, and logistic regression classifiers were evaluated. Among them, the support vector machine classifier shows the best performance with the classification accuracy of 81 %. The use of spectral band feature set alone(accuracy of 76 %) shows better performance than that of non-linear recurrence pattern feature set alone(accuracy of 67 %). The support vector machine classifier with hybrid combination of non-linear and spectral analysis can be used in later designing attention-related devices.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.5
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• pp.133-142
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• 2004

Recently, the growth of Internet and a variety of multimedia services through Internet increasingly demands high-speed packet transmission, the new routing function, and QoS guarantee on conventional routers. Thus, a new switching mechanical called the MPLS(Multi-Protocol Label Switching), was proposed by IETF(Internet Engineering Task Force) as a solution to meet these demands. In addition the deployment of MPLS network supporting Differentiated Services is required. In this paper, we propose the architecture of the MPLS switch supporting Differentiated Services in the MPLS-based network. The traffic conditioner consists of a classifier, a meter, and a marker. The VOQ-PHB module, which combines input Queue with each PHB queue, is implemented to utilize the resources efficiently. It employs the Priority-iSLIP scheduling algorithm to support high-speed switching. We have designed and verified the new and fast hardware architecture of VOQ-PHB and the traffic conditioner for QoS and high-speed switching using NS-2 simulator. In addition, the proposed architecture is modeled in VHDL, synthesized and verified by the VSS analyzer from SYNOPSYS. Finally, to justify the validity of the hardware architecture, the proposed architecture is placed and routed using Apollo tool.

• Journal of KIISE:Software and Applications
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• v.36 no.9
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• pp.767-776
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• 2009

A software birthmark is a set of characteristics that are extracted from a program itself to detect code theft. A dynamic API birthmark is extracted from the run-time API call sequences of a program. The dynamic Windows API birthmarks of Tamada et al. are extracted from API call sequences during the startup period of a program. Therefore. the dynamic birthmarks cannot reflect characteristics of main functions of the program. In this paper. we propose a functional unit birthmark(FDAPI) that is defined as API call sequences recorded during the execution of essential functions of a program. To find out that some functional units of a program are copied from an original program. two FDAPIs are extracted by executing the programs with the same input. The FDAPIs are compared using the semi-global alignment algorithm to compute a similarity between two programs. Programs with the same functionality are compared to show credibility of our birthmark. Binary executables that are compiled differently from the same source code are compared to prove resilience of our birthmark. The experimental result shows that our birthmark can detect module theft of software. to which the existing birthmarks of Tamada et al. cannot be applied.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.61-68
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• 2004

Now, the representative researching trends of view managements for improving the query processing in multi-database system are focused on the materialized view mechanism and the signature view index mechanism. But when we compare with both mechanisms, the former mechanism's access time is faster than one of the latter's, and needs large space. The latter mechanism needs small space and the access time is slower than one of the former. These mechanisms are trade-off each other. Therefore, in case of query process using the view management, we are to improve the system performance and to reduce the access cost of disk input and output by suggesting a new mechanism mixing both the materialized view mechanism and the signature view index mechanism. We suggested that the structure of metadata and the algorithm about the new mired mechanism.

• The KIPS Transactions:PartA
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• v.13A no.1 s.98
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• pp.79-86
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• 2006

Recently the tagSNP selection problem has been researched for reducing the cost of association studies between human's diversities and SNPs. General approach for this problem is that all of SNPs are separated into appropriate blocks and then tagSNPs are chosen in each block. Marsel in this paper is the system that involved the concept of linkage disequilibrium for overcoming the problem that the existing block partitioning approaches have short of biological meanings. In most approaches, the contiguous regions, which recombinations have LD coefficient |D'| and then tagSNP selection step is performed. And MarSel guarantees the minimum tagSNP selection using entropy-based optimal selection algorithm when tagSNPs are chosen in each block, and enables chromosome-level association studies using efficient memory management technique when input is very large-scale dataset that is impossible to be processed in the existing systems.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.15-26
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• 2002

Most work on multimedia storage systems has assumed that client will be serviced using a round-robin strategy. The server services the clients in rounds and each client is allocated a time slice within that round. Furthermore, most such algorithms are evaluated on the basis of a tightly coupled cost function. This is the basis of well-known algorithm such as FCFS, SCAN, SCAN-EDF, etc. In this paper, we describe a scheduling module called Request Unifier(RU) that takes as input, a set of client request, and a set of constraints on the desired performance such as client waiting time or maximum disk bandwidth, and a cost function. It produces as output a Unified Read Request(URR), telling the storage server which data items to read and when these data items to be delivered to the clients. Given a cost function, a URR is optimal if there is no other URR satisfying the constraints with a lower cost. We present three algorithms in this paper that can accomplish this kind of request merging and compare their performance through an experimental evaluation.

• Journal of KIISE
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• v.42 no.6
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• pp.748-754
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• 2015

This paper proposes a sequential state estimation model consisting of continuous and discrete variables, as a way of generalizing all discrete-state factorial HMM, and gives a design of gait motion model based on the idea. The discrete state variable implements a Markov chain that models the gait dynamics, and for each state of the Markov chain, we created a Gaussian process over the space of the continuous variable. The Markov chain controls the switching among Gaussian processes, each of which models the rotation or various views of a gait state. Then a particle filter-based algorithm is presented to give an approximate filtering solution. Given an input vector sequence presented over time, this finds a trajectory that follows a Gaussian process and occasionally switches to another dynamically. Experimental results show that the proposed model can provide a very intuitive interpretation of video-based gait into a sequence of poses and a sequence of posture states.

• Journal of Computing Science and Engineering
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• v.5 no.2
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• pp.111-120
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• 2011

Data mining algorithms should exploit new hardware technologies to accelerate computations. Such goal is difficult to achieve in database management system (DBMS) due to its complex internal subsystems and because data mining numeric computations of large data sets are difficult to optimize. This paper explores taking advantage of existing multithreaded capabilities of multicore CPUs as well as caching in RAM memory to efficiently compute summaries of a large data set, a fundamental data mining problem. We introduce parallel algorithms working on multiple threads, which overcome the row aggregation processing bottleneck of accessing secondary storage, while maintaining linear time complexity with respect to data set size. Our proposal is based on a combination of table scans and parallel multithreaded processing among multiple cores in the CPU. We introduce several database-style and hardware-level optimizations: caching row blocks of the input table, managing available RAM memory, interleaving I/O and CPU processing, as well as tuning the number of working threads. We experimentally benchmark our algorithms with large data sets on a DBMS running on a computer with a multicore CPU. We show that our algorithms outperform existing DBMS mechanisms in computing aggregations of multidimensional data summaries, especially as dimensionality grows. Furthermore, we show that local memory allocation (RAM block size) does not have a significant impact when the thread management algorithm distributes the workload among a fixed number of threads. Our proposal is unique in the sense that we do not modify or require access to the DBMS source code, but instead, we extend the DBMS with analytic functionality by developing User-Defined Functions.

• The Journal of the Korea Contents Association
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• v.8 no.6
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• pp.16-25
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• 2008

Today, mobile phone is a necessity of modern life. For that reason, we suggest a particular system of a mobile phone which take a picture of music score image and automatically play it without any technical knowledges about the music score information. This experiment makes midi, acknowleging separate symbols via preprocessing to music score image taken. This paper utilizes 11 sorts of the score image taken by a mobile phone camera for this experiment. Through this method we suggest, as much as 98% on average takes place, which is very high recognizing ratio. Also, as we introduce this system in a mobile phone by porting, it takes 8.63 seconds on average to create midi following input of images.