• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12B
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• pp.1749-1757
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• 2010

This paper considers the cost minimization problem to satisfy QoS (Quality of Service) requirements for a given network, in particular when communication resources to each link can be additionally assigned. For the purpose of quantifying QoS requirements such as data transfer delay and packet loss, we introduce the cost function considering both the link utilization factor and the additionally assigned resource. To minimize this cost function, we firstly formulate a Basic Capacity Planning (BCP) problem, a special case of Network Utility Maximization (NUM). We show that the solution of this BCP problem cannot be optimal via a counter example. In this paper, we suggest the cross-layer design of both additionally assigned resource and routing path, whose initial values are set to the result of BCP problem. This cross-layer design is based on a heuristic approach which presents an effective way to plan how much communication resources should be added to support the QoS requirements in future. By simulation study, we investigate the convergence of the cost function in a more general network topology as well as in a given simple topology.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.215-221
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• 2006

This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems such as the structural instability, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control were fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system by employing only single algorithm since the system usually includes multiple nonlinearities. In this paper, a switching Pill is considered for a control of saturation and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between the results of simulation and experiment, and then the switching Pill gains are determined using genetic algorithm with some heuristic approach. The performance of the switching Pill controller for saturation and the dual feedback for backlash control is investigated through the simulation. Finally, it is shown that the implemented control system has good results and can be applied to the real humanoid robot system ISHURO.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.221-226
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• 2004

Ant Colony System(ACS) Algorithm is new meta-heuristic for hard combinational optimization problem. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. Recently, various methods and solutions are proposed to solve optimal solution of graph coloring problem that assign to color for adjacency node($v_i, v_j$) that they has not same color. In this paper introducing ANTCOL Algorithm that is method to solve solution by Ant Colony System algorithm that is not method that it is known well as solution of existent graph coloring problem. After introducing ACS algorithm and Assignment Type Problem, show the wav how to apply ACS to solve ATP And compare graph coloring result and execution time when use existent generating functions(ANT_Random, ANT_LF, ANT_SL, ANT_DSATUR, ANT_RLF method) with ANT_XRLF method that use XRLF that apply Randomize to RLF to solve ANTCOL. Also compare graph coloring result and execution time when use method to add re-search to ANT_XRLF(ANT_XRLF_R) with existent generating functions.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.117-129
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• 2008

The cost-based scheduling work has been done in both the Operations Research (OR) and Artificial Intelligence (AI) literature. To deal with more realistic problems, AI-based heuristic scheduling approach with non-regular performance measures has been studied. However, there has been little research effort to develop a full inter-job cost propagation algorithm (CPA) for different jobs having multiple downstream and upstream activities. Without such a CPA, decision-making in scheduling heuristics relies upon local, incomplete cost information, resulting in poor schedule performance from the overall cost minimizing objective. For such a purpose, we need two types of CPAs : intra-job CPA and inter-job CPA. Whenever there is a change in cost information of an activity in a job in the process of scheduling, the intra-job CPA updates cost curves of other activities connected through temporal constraints within the same job. The inter-job CPA extends cost propagation into other jobs connected through precedence relationships. By utilizing the cost information provided by CPAs, we propose cost-based scheduling heuristics that attempt to minimize the total schedule cost. This paper develops inter-job CPAs that create and update cost curves of each activity in each search state, and propagate cost information throughout a whole network of temporal constraints. Also we propose various cost-based scheduling heuristics that attempt to minimize the total schedule cost by utilizing the cost propagation algorithm.

• Journal of Korean Society of Steel Construction
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• v.18 no.2
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• pp.213-223
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• 2006

Conventional truss optimization approaches, while often sophisticated and computationally intensive, have been applied to simple, minimum weight-cost models. These approaches do not perform well when applied to real-world trusses, which have costmodels that are complex and which often involve multiple objectives. Thus, this paper describes the optimization strategies that a clustering technique, which identifies members that are likely to have the same product type, uses for the optimal design of truss structures with real- world cost functions that consider the costs on the weight of the truss, the number of products in the design, the number of joints in the structures, and the costs required in the site.At first, the clustering technique is applied to identify the members and to generate a proper initial solution. A simple taboo search technique is then used, which attempts to generate the optimal solution by starting with the solution from the previous technique. For example, the proposed approach is a plied to a typical problem and to a problem similar to relative performances. The results show that this algorithm generates not only better-quality solutions but also more efficient ones

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.658-668
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• 2011

Over the past decade, the improvement of communications technologies and the rapid spread of www (World Wide Web) have brought on the exponential growth of users using Internet and real time multimedia multicast services like video conferencing, tele-immersive virtual reality, and Internet games. The dense-wavelength division multiplexing (DWDM) networks have been widely accepted as a promising approach to meet the ever-increasing bandwidth demands of Internet users, especially in next generation Internet backbone networks for nation-wide or global coverage. A major challenge in the next generation Internet backbone networks based on DWDM technologies is the resolution of the multicasting RWA (Routing and Wavelength Assignment) problem; given a set of wavelengths in the DWDM network, we set up light-paths by routing and assigning a wavelength for each connection so that the multicast connections are set-upped as many as possible. Finding such optimal multicast connections has been proven to be Non-deterministic Polynomial-time-complete. In this paper, we suggest a new heuristic multicast routing and wavelength assignment method for multicast sessions called DVS-PMIPMR (Differentiated Virtual Source-based Priority Minimum Interference Path Multicast Routing algorithm). We measured the performance of the proposed algorithm in terms of number of wavelength and wavelength channel. The simulation results demonstrate that DVS-PMIPMR algorithm is superior to previous multicast routing algorithms.

• Korea Science and Art Forum
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• v.37 no.2
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• pp.35-46
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• 2019

The purpose of this study was to develop a hybrid model forecasting the optimal number of employees for the hotel MICE and investigate indicators' reliability and validity empirically. The dominant approach of manpower planning has long been conducted based on heuristic experience in the field of Hotel and MICE. There is little research on the manpower planning and forecasting in the hotel and MICE studies. However, it is significantly important to ensure how many the optimal number of employees are calculated to meet the goals of the company as well as the expectation of their customers. A focus group interview was used to collect data through a series of surveys. A total of 289 samples were collected to test validity of finalized indicators for forecasting the optimal number of employees for the Hotel MICE. The study developed 15 quantitative indicators and 19 qualitative indicators to forecasting the optimal number of employees for the Hotel MICE, based on three types of groups such as 'service-oriented', 'stability-oriented', and 'profitability-oriented' hotel company The study revealed the econometrics formula for the practical application for this field.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.189-200
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• 2022

In today's digital world, smartphones and web-based applications have gained remarkable importance throughout the globe. These smart applications are playing a very significant role in maintaining a powerful business. As well as, they are helping a lot to expand these businesses via social networks. Social media networks such as Instagram, Facebook, Twitter, and LinkedIn are playing a prominent role to promote the companies. In the hospitality sector, most of the companies are running their hotel booking systems by utilizing mobile applications and a web-based infrastructure, but usability issues still exist. This study has been conducted specifically to tackle the usability issues of hotel booking systems and the best utilization of social networks to promote the business. TripAdvisor was selected as an authentic source for selecting those systems and two international hotels are selected for this study. The first step is to identify different hotel booking systems. In the second step, the user's satisfaction level was measured for the selected systems by performing the System Usability Scale (SUS, Quick & Dirty) approach. Additionally, by which source (social media or personal relations) they found these hotels. It is found that the SUS rating for both systems is below the acceptable level of usability. The Mean SUS for hotel 1 is found at 55.25 and 51.2 for hotel 2. The third step was to identify the user interface (UI) issues, and heuristic evaluation is performed for this. The experts identified the UI issues on the basis of their experience. The major issues were related to the visibility of system status, error prevention, flexibility and efficiency of use. Depending upon the identified issues, an interactive UI (prototype) for the selected web-based applications was proposed. This prototype is mainly based on the user's perspective. This prototype can be used for improving the UI of the selected systems which is based on the user's perspective. During the process of verifying the satisfaction level, it is revealed that the targeted audience is not able to use these systems efficiently and effectively. The reason behind this is the negligence of usability guidelines throughout the process of design and development of these hotel booking systems. Therefore, it is highly recommended that the usability of these systems should be evaluated and redesigned, based on expert opinions. It has also been observed that the reviews/ feedback of customers has spread a negative impact through social networks.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.49-63
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• 2024

Objective : The purpose of this study was to investigate parental perspectives on cognitive rehabilitation using a combination of phenomenological research methodology and word cloud analysis. Methods : Interviews were conducted with five parents of children with developmental disabilities. Word cloud analysis was conducted using Python, and five researchers analyzed the meaning units and themes using phenomenological methods. Words with high frequency were considered as a heuristic tool. Results : A total of 43 meaning units and nine components related to the phenomenon of cognitive rehabilitation were derived, and three themes were finalized. The main themes encompassed the definition of cognitive rehabilitation, challenges associated with cognitive rehabilitation, and factors influencing the selection of a cognitive rehabilitation institute. Cognitive rehabilitation emerged as a treatment focused on improving learning, daily functioning, and cognitive abilities in children with developmental disabilities. The perceived issues with cognitive rehabilitation pertained to treatment methods, therapist expertise, and associated costs. In addition, parents highlighted the importance of therapist expertise, humane personality, and affordability of cost and schedule when choosing a cognitive rehabilitation institute. Conclusion : Parents expressed expectations for substantial improvements in their children's daily functioning through cognitive rehabilitation. However, challenges were identified in clinical practices. Going forward, we expect that cognitive rehabilitation will evolve into a better therapeutic support service addressing the concerns raised by parents.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.214-224
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• 2024

Sonobuoys are disposable devices that utilize sound waves for information gathering, detecting engine noises, and capturing various acoustic characteristics. They play a crucial role in accurately detecting underwater targets, making them effective detection systems in anti-submarine warfare. Existing sonobuoy deployment methods in multistatic systems often rely on fixed patterns or heuristic-based rules, lacking efficiency in terms of the number of sonobuoys deployed and operational time due to the unpredictable mobility of the underwater targets. Thus, this paper proposes an optimal sonobuoy placement strategy for Unmanned Aerial Vehicles (UAVs) to overcome the limitations of conventional sonobuoy deployment methods. The proposed approach utilizes reinforcement learning in a simulation-based experimental environment that considers the movements of the underwater targets. The Unity ML-Agents framework is employed, and the Proximal Policy Optimization (PPO) algorithm is utilized for UAV learning in a virtual operational environment with real-time interactions. The reward function is designed to consider the number of sonobuoys deployed and the cost associated with sound sources and receivers, enabling effective learning. The proposed reinforcement learning-based deployment strategy compared to the conventional sonobuoy deployment methods in the same experimental environment demonstrates superior performance in terms of detection success rate, deployed sonobuoy count, and operational time.