• The Journal of the Acoustical Society of Korea
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• v.24 no.8
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• pp.498-504
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• 2005

We introduce a Korean speech recognition platform (ECHOS) developed for education and research Purposes. ECHOS lowers the entry barrier to speech recognition research and can be used as a reference engine by providing elementary speech recognition modules. It has an easy simple object-oriented architecture, implemented in the C++ language with the standard template library. The input of the ECHOS is digital speech data sampled at 8 or 16 kHz. Its output is the 1-best recognition result. N-best recognition results, and a word graph. The recognition engine is composed of MFCC/PLP feature extraction, HMM-based acoustic modeling, n-gram language modeling, finite state network (FSN)- and lexical tree-based search algorithms. It can handle various tasks from isolated word recognition to large vocabulary continuous speech recognition. We compare the performance of ECHOS and hidden Markov model toolkit (HTK) for validation. In an FSN-based task. ECHOS shows similar word accuracy while the recognition time is doubled because of object-oriented implementation. For a 8000-word continuous speech recognition task, using the lexical tree search algorithm different from the algorithm used in HTK, it increases the word error rate by $40\%$ relatively but reduces the recognition time to half.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.41-49
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• 2022

The Internet Engineering Task Force (IETF) has standardized RPL (IPv6 Routing Protocol for Low-power Lossy Network) as a routing protocol for Low Power and Lossy Networks (LLNs), a low power loss network environment. RPL creates a route through an Objective Function (OF) suitable for the service required by LLNs and builds a Destination Oriented Directed Acyclic Graph (DODAG). Existing studies check the residual energy of each node and select a parent with the highest residual energy to build a DODAG, but the energy exhaustion of the parent can not avoid the network disconnection of the children nodes. Therefore, this paper proposes EC-RPL (Enhanced Connectivity-RPL), in which ta node leaves DODAG in advance when the remaining energy of the node falls below the specified energy threshold. The proposed protocol is implemented in Contiki, an open-source IoT operating system, and its performance is evaluated in Cooja simulator, and the number of control messages is compared using Foren6. Experimental results show that EC-RPL has 6.9% lower latency and 5.8% fewer control messages than the existing RPL, and the packet delivery rate is 1.7% higher.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.51-60
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• 2016

Embedded software has requirements such as real-time and environment independency. The real-time requirement is affected from worst-case execution time of loaded tasks. Therefore, to guarantee real-time requirement, we need to determine a program's worst-case execution time using static analysis approach. However, the existing methods for worst-case execution time analysis do not consider the environment independency. Thus, in this paper, in order to provide environment independency, we propose a method for measuring task's execution time from the source codes. The proposed method measures the execution time through the control flow graph created from the source codes instead of the executable codes. However, the control flow graph created from the source code does not have information about execution time. Therefore, in order to provide this information, the proposed method identifies the relationships between statements in the source code and instructions in the executable code. By parameterizing those parts that are dependent on processors based on the relationships, it is possible to enhance the flexibility of the tool that measures the worst-case execution time.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.60-67
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• 2009

Analyzing protein-protein interactions(PPI) is an important task in bioinformatics as it can help in new drugs' discovery process. However, due to vast amount of PPI data and their complexity, efficient visualization of the data is still remained as a challenging problem. We have developed efficient and effective visualization system that integrates Gene Ontology(GO) and PPI network to provide better insights to scientists. To provide efficient data visualization, we have employed dynamic interactive graph drawing methods and context-based browsing strategy. In addition, quick and flexible cross-reference system between GO and PPI; LCA(Least Common Ancestor) finding for GO; and etc are supported as special features. In terms of interface, our visualization system provides two separate graphical windows side-by-side for GO graphs and PPI network, and also provides cross-reference functions between them.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.38-46
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• 2004

Image segmentation is the task which partitions the image into meaningful regions and considered to be one of the most important steps in computer vision and image processing. Image segmentation is also widely used in object-based video compression such as MPEG-4 to extract out the object regions from the given frame. Watershed algorithm is frequently used to obtain the more accurate region boundaries. But, it is well known that the watershed algorithm is extremely sensitive to gradient noise and usually results in oversegmentation. To solve such a problem, we propose an image segmentation method which is robust to noise by using stabilized inverse diffusion equation (SIDE) and is more efficient in segmentation by employing multiresolution approach. In this paper, we apply both the region projection method using labels of adjacent regions and the region merging method based on region adjacency graph (RAG). Experimental results on noisy image show that the oversegmenation is reduced and segmentation efficiency is increased.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.293-307
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• 2004

We consider the problem of scheduling tasks of a precedence constrained task graph, where each task has its execution time and deadline, onto a set of identical processors in a way that simultaneously minimizes the number of processors required and the total tardiness of tasks. Most existing approaches tend to focus on the minimization of the total tardiness of tasks. In another methods, solutions to this problem are usually computed by combining the two objectives into a simple criterion to be optimized. In this paper, the minimization is carried out using a multiobjective genetic algorithm (GA) that independently considers both criteria by using a vector-valued cost function. We present various GA components that are well suited to the problem of task scheduling, such as a non-trivial encoding strategy. a domination-based selection operator, and a heuristic crossover operator We also provide three local improvement heuristics that facilitate the fast convergence of GA's. The experimental results showed that when compared to five methods used previously, such as list-scheduling algorithms and a specific genetic algorithm, the Performance of our algorithm was comparable or better for 178 out of 180 randomly generated task graphs.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.83-102
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• 2018

The process model of emotion regulation suggests that cognitive reappraisal and expressive suppression engage at different time points in the regulation process. Although multiple brain regions and networks have been identified for each strategy, no articles have explored changes in network characteristics or network connectivity over time. The present study examined (a) the whole-brain network and six other resting-state networks, (b) their modularity and global efficiency, which is an index of the efficiency of information exchange across the network, (c) the degree and betweenness centrality for 160 brain regions to identify the hub nodes with the most control over the entire network, and (d) the intra-network and inter-network functional connectivity (FC). Such investigations were performed using a traditional large-scale FC analysis and a relatively recent sliding window correlation analysis. The results showed that the right inferior orbitofrontal cortex was the hub region of the whole-brain network for both strategies. The present findings of temporally altering functional activity of the networks revealed that the default mode network (DMN) activated at the early stage of reappraisal, followed by the task-positive networks (cingulo-opercular network and fronto-parietal network), emotion-processing networks (the cerebellar network and DMN), and sensorimotor network (SMN) that activated at the early stage of suppression, followed by the greater recruitment of task-positive networks and their functional connection with the emotional response-related networks (SMN and occipital network). This is the first study that provides neuroimaging evidence supporting the process model of emotion regulation by revealing the temporally varying network efficiency and intra- and inter-network functional connections of reappraisal and suppression.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.413-421
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• 2005

Intra-block remarshalling is the task of rearranging into some target bays those containers which are scattered within around the block. If multiple transfer cranes installed in the block are all used together we may be able to complete the remarshalling task as early as possible. However, when multiple cranes are used simultaneously, there may occur significant delays if we do not carefully consider interferences between the cranes at the time of scheduling. Especially, delays caused by interferences occur more frequently in case of using non-crossing cranes. This paper presents an efficient heuristics method for assigning moves of containers to each crane and for determining an appropriate container moving order in a manner sensitive to the interferences. Simulation experiments have shown that the proposed method can effectively reduce delays in various environments.

• Journal of Navigation and Port Research
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• v.29 no.5 s.101
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• pp.447-455
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• 2005

Intra-block remarshalling is the task of rearranging into some target bays those containers which are scattered within around the block. If multiple transfer cranes installed in the block are all used together we may be able to complete the remarshalling task as early as possible. However, when multiple cranes are used simultaneously, there may occur significant delays if we do not carefully consider interferences between the cranes at the time of scheduling. Especially, delays caused by interferences occur more frequently in case of using non-crossing cranes. This paper presents an efficient heuristic method for assigning moves of containers to each crane and for determining an appropriate container moving order in a manner sensitive to the interferences. Simulation experiments have shown that the proposed method can effectively reduce delays in various environments.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.261-274
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• 1999

Recently, automated business processing systems, so called workflow systems, have been studied. have been studied. even though each task has noticible duration inherently, most of previous models regard it as a simple finite automation where state transitions occur instantly. In this paper, we propose a modeling method for workflow each of whose component task has minimum processing time and due-date. Firstly we provide a priority function to choose the proper alternatives when tasks fail before their due-date. The priority function considers the time-relevant factor and the semantic compatibility level to decide the best alternative. secondly, we identify six different types of execution requirements for tasks with noticible durations. They are serial, parallel, simultaneous start simultaneous termination, interleaved and nested dependency. Note that previous models deal with only serial execution and parallel execution. Lastly, we also propose graph-based methods to detect logical conflicts in time constraint-based workflow specifications.