• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.832-842
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• 2020

The coordination control of multiple Underactuated Underwater Vehicles (UUVs) moving in three dimensional space is investigated in this paper. The coordinated path following control task is decomposed into two sub tasks, that is, path following control and coordination control. In the spatial curve path following control task, path following error dynamics is build in the Serret-Frenet coordinate frame. The virtual reference object can be chosen freely on the desired spatial path. Considering the speed of the UUV, the line-of-sight navigation is introduced to help the path following errors quickly converge to zero. In the coordination control sub task, the communication topology of multiple UUVs is described by the graph theory. The speed of each UUV is adjusted to achieve the coordination. The path following system and the coordination control system are viewed as the feedback connection system. Input-to-state stable of the coordinated path following system can be proved by small gain theorem. The simulation experiments can further demonstrate the good performance of the control method.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.17-23
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• 2022

Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.106-118
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• 2021

The field of brain science (or neuroscience in a broader sense) has inspired researchers in artificial intelligence (AI) for a long time. The outcomes of neuroscience such as Hebb's rule had profound effects on the early AI models, and the models have developed to become the current state-of-the-art artificial neural networks. However, the recent progress in AI led by deep learning architectures is mainly due to elaborate mathematical methods and the rapid growth of computing power rather than neuroscientific inspiration. Meanwhile, major limitations such as opacity, lack of common sense, narrowness, and brittleness have not been thoroughly resolved. To address those problems, many AI researchers turn their attention to neuroscience to get insights and inspirations again. Biologically plausible neural networks, spiking neural networks, and connectome-based networks exemplify such neuroscience-inspired approaches. In addition, the more recent field of brain network analysis is unveiling complex brain mechanisms by handling the brain as dynamic graph models. We argue that the progress toward the human-level AI, which is the goal of AI, can be accelerated by leveraging the novel findings of the human brain network.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.73-79
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• 2021

Recently, in the field of computer animation, a method for generating motion using deep learning has been studied away from conventional finite-state machines or graph-based methods. The expressiveness of the network required for learning motions is more influenced by the diversity of motion contained in it than by the simple length of motion to be learned. This study aims to find an efficient network structure when the types of motions to be learned are diverse. In this paper, we train and compare three types of networks: basic fully-connected structure, mixture of experts structure that uses multiple fully-connected layers in parallel, recurrent neural network which is widely used to deal with seq2seq, and transformer structure used for sequence-type data processing in the natural language processing field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4364-4384
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• 2021

The dynamic network state and the mobility of the terminals make the service function chain (SFC) orchestration mechanisms based on static and deterministic assumptions hard to be applied in SDN/NFV mobile edge computing networks. Designing dynamic and online SFC orchestration mechanism can greatly improve the execution efficiency of compute-intensive and resource-hungry applications in mobile edge computing networks. In order to increase the overall profit of service provider and reduce the resource cost, the system running time is divided into a sequence of time slots and a dynamic orchestration scheme based on an improved column generation algorithm is proposed in each slot. Firstly, the SFC dynamic orchestration problem is formulated as an integer linear programming (ILP) model based on layered graph. Then, in order to reduce the computation costs, a column generation model is used to simplify the ILP model. Finally, a two-stage heuristic algorithm based on greedy strategy is proposed. Four metrics are defined and the performance of the proposed algorithm is evaluated based on simulation. The results show that our proposal significantly provides more than 30% reduction of run time and about 12% improvement in service deployment success ratio compared to the Viterbi algorithm based mechanism.

• Asia pacific journal of information systems
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• v.17 no.3
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• pp.1-24
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• 2007

With the development of information technology (IT), various information systems (IS) such as Web-based systems and mobile systems have appeared utilizing different technologies. However, recent studies on IS use and user satisfaction rarely account for technological differences among IS and environmental characteristics where IS are intended to be used. The purpose of this research is to investigate the determinants of the use of Web-based ticketing systems for cultural activities and to empirically validate their relationships. Environmental psychology suggests that human beings respond to external stimuli from environments with their emotions, and their emotional states influence human actions, e.g., IS use in this research. Applying environmental psychology to the use of Web-based systems in the culture and entertainment industry, we propose that web site characteristics first influence a user's internal state of mind (i.e., flow) and then the flow state influences the IS use. Studies related to the state of flow collectively affirm the key role played by the flow construct in shaping individual attitudes and behaviors toward IS. Users' flow states are captured by their shopping enjoyment, perceived behavioral control, and the level of concentration on the IS use. Referring to social presence theory, we have included such web site characteristics as content quality, context of web site, and community quality. In our research model, a second order construct is utilized to represent web site quality, because flow theory suggests that holistic experiences with web-based systems (rather than individual characteristics of the web site) are important in explaining the IS use. Further, we have included trust as another important factor influencing the IS use since business transactions on the web encompass higher uncertainty comparing to offline transactions. In order to test our hypotheses, we have conducted an online survey which results in 1,141 valid responses in the final sample. The data were collected from respondents who have experiences in Internet ticketing systems. Although it was a convenient sample, the sample represents a wide variety of user demographics. Validity and reliability of the research instrument were tested and research hypotheses were examined using PLS Graph 3.0. The results indicate that web site characteristics significantly influence the level of user concentration, user's enjoyment in shopping, and perceived behavioral control. Further, the use of Internet ticketing systems is influenced by users' flow states and trust in the web channel. User satisfaction is turned out to be affected by the use of Internet ticketing systems. Unlike extant research on the relationship between web site characteristics and its use, our study has found that, in the culture and entertainment industry, the impact of web site characteristics on IS use is mediated by a user's flow state. This finding has a practical implication that web site design should include as many features that enhance shopping enjoyment and concentration. Other practical implications of these findings and future research implications are also discussed.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.103-111
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• 2023

Consensus, that aims to converge the states of agents to the same states through information exchanges between agents, has been widely studied to control the multi-agent systems. In real systems, the measurement variables of each agent may be different, the loss of information across communication may occur, and the different networks for each state may need to be constructed for safety. Moreover, the input saturation and the disturbances in the system may cause instability. Therefore, this paper studies the PID(Proportional-Integral-Derivative)-based consensus control to achieve the swarm behavior of the multi-agent systems considering the heterogeneous state information, the input saturations, and the disturbances. Specifically, we consider the multiple follower agents and the single leader agent modeled by the second-order systems, and investigate the conditions to achieve the consensus based on the stability of the error system. It is confirmed that the proposed algorithm can achieve the consensus if only the connectivity of the position graph is guaranteed. Moreover, by extending the consensus algorithm, we study the formation control problem for the multi-agent systems. Finally, the validity of the proposed algorithm was verified through the simulations.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.16-27
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• 2011

Embryo is a very early stage of the development of multicellular organism such as animals and plants. It is an important research target for studying ontogeny because the fundamental body system of multicellular organism is determined during an embryo state. Researchers in the developmental biology have a large volume of embryo image databases for studying embryos and they frequently search for an embryo image efficiently from those databases. Thus, it is crucial to organize databases for their efficient search. Hierarchical clustering methods have been widely used for database organization. However, most of previous algorithms tend to produce a highly skewed tree as a result of clustering because they do not simultaneously consider both the size of a cluster and the number of objects within the cluster. The skewed tree requires much time to be traversed in users' search process. In this paper, we propose a method that effectively organizes a large volume of embryo image data in a balanced tree structure. We first represent embryo image data as a similarity-based graph. Next, we identify clusters by performing a graph partitioning algorithm repeatedly. We check constantly the size of a cluster and the number of objects, and partition clusters whose size is too large or whose number of objects is too high, which prevents clusters from growing too large or having too many objects. We show the superiority of the proposed method by extensive experiments. Moreover, we implement the visualization tool to help users quickly and easily navigate the embryo image database.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.209-218
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• 2012

Recently, the Field Programmable Stateful Logic Array (FPSLA) was proposed as one of the most promising system integration technologies which will extend the life of the Moore's law. This work is the first proposal of the FPSLA design automation flow, and the approaches to logic synthesis, synchronization, physical mapping, and automatic placement of the FPSLA designs. The synchronization at each gate for pipelining determines the x-coordinates of cells, and reduces the placement to 1-dimensional problems. The objective function and its gradients for the non-linear optimization of the net length and placement density have been remodeled for the reduced global placement problem. Also, a recursive algorithm has been proposed to legalize the placement by relaxing the density overflow of bipartite bin groups in a top-down hierarchical fashion. The proposed model and algorithm are implemented, and validated by applying them to the ACM/SIGDA benchmark designs. The output state of a gate in an FPSLA needs to be duplicated so that each fanout gate can be connected to a dedicated copy. This property has been taken into account by merging the duplicated nets into a hyperedge, and then, splitting the hyperedge into edges as the optimization progresses. This yields additional 18.4% of the cell count reduction in the most dense logic stage. The practicality of the FPSLA can be further enhanced primarily by incorporating into the logic synthesis the constraint to avoid the concentrated fains of gates on some logic stages. In addition, an efficient algorithm needs to be devised for the routing problem which is based on a complicated graph. The graph models the nanowire crossbar which is trimmed to be embedded into the FPSLA fabric, and therefore, asymmetric. These CAD tools can be used to evaluate the fabric efficiency during the architecture enhancement as well as automate the design.

• 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.