• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.147-154
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• 2010

This paper suggests new route plan cost calculation and cost-effective route plan algorithm and architecture for the new city traffic information system when it is operated nationwide. New algorithm and architecture estimates cost with traffic speeds which is supported for all different lanes, stratifies logical layer which process different levels' traffic information with diverse traffic patterns and provides different traffic information in the few levels. Also suggested new algorithm supports drivers' customized traffic information through both-way communications and plans routes effectively based on the distance between drivers' start position and destination and different levels which start and end position located. It proposes additional research items and requirement for integration between different cities' traffic information system which the national police agency invested and led.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.219-227
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• 2008

The DEVS (Discrete Event Systems Specification) formalism supports specification of discrete event models in a hierarchical modular manner. MATLAB/Simulink is widely used for modeling, simulating and analyzing continuous and discrete time systems. This paper proposes a realization of the DEVS formalism in MATLAB/ Simulink. The proposed design enables to use a great amount of mathematical packages and functions included in MATLAB /Simulink. The design is also employed as real time simulation and hybrid system simulation which is a mixture of continuous systems and discrete event systems. The paper introduces Simulink-DEVS model, in which a simulation algorithm is embedded. The model consists of a Simulink-atomic model and a Simulink-coupled model. In addition, the time advance algorithm to simulate the model is suggested. The algorithm handles the time synchronization and the accommodation of different concepts specific to continuous and discrete event models. Two experimental results are presented for a pure discrete event model and a hybrid model.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.211-218
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• 2004

In a large owner organization, a program manager of multiple maintenance and remodeling projects has experienced increasing scale and complexity of coordinating the M/R projects with in-house technicians who belong to multiple trade shops. This paper proposes a dual-level hierarchical planning strategy that consists of a program master plan in the long-term horizon and a master construction schedule in an operational scheduling window. A rolling horizon approach to the program master plan is proposed to deal with the external uncertainty of unknown stream of project requests. A resource-constrained scheduling algorithm is developed to generate the master construction schedule in a scheduling window. During development of the algorithm, more emphasis is placed on long-term organizational resource continuity, especially flow management of program constraint resources, than ephemeral events of an individual activity and project. Monte Carlo simulation experiments of three scheduling windows are used to evaluate the relative performance of the proposed scheduling algorithm against three popular scheduling heuristics for resource-constrained multiple projects.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.550-557
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• 2007

We predict a context of various structures by using Bayesian Networks Algorithms, Three-Dimensional Structures Algorithms and Genetic Algorithms. However, these algorithms have unavoidable problems when providing a context-aware service in reality due to a lack of practicality and the delay of process time in real-time environment. As far as context-aware system for specific purpose is concerned, it is very hard to be sure about the accuracy and reliability of prediction. This paper focuses on reasoning and prediction technology which provides a stochastic mechanism for context information by incorporating various context information data. The objective of this paper is to provide optimum services to users by suggesting an intellectual reasoning and prediction based on hierarchical context information. Thus, we propose a design of user location prediction algorithm using sequential matching with n-size flexible window scheme by taking user's habit or behavior into consideration. This algorithm improves average 5.10% than traditional algorithms in the accuracy and reliability of prediction using the Flexible Window Scheme.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.831-834
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• 2011

LEACH(One of the leading algorithms in the field of WSN) for the life of the system, even by the number of all nodes to ensure that the cluster header. However, each round does not guarantee a certain number of cluster header. So sometimes cluster header is elected of small number or not elected. If cluster header number is to small, takes a heavy load on cluster header. And empty cluster is occur depending on the location of the cluster header. The algorithm proposed in this paper, the area of interest is divided into sectors. And randomly, cluster header be elected one the in each sector. When clustering the sensor nodes will belong to the nearest cluster header. So clustering is independent of the sector. This algorithm is guarantee a certain number of cluster header in each round. And has prevent occurrence of empty cluster.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1120-1131
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• 2016

In this paper, we propose a smoker recognition algorithm, detecting smokers in a video sequence in order to prevent fire accidents. We use description-based method in hierarchical approaches to recognize smoker's activity, the algorithm consists of background subtraction, object detection, event search, event judgement. Background subtraction generates slow-motion and fast-motion foreground image from input image using Gaussian mixture model with two different learning-rate. Then, it extracts object locations in the slow-motion image using chain-rule based contour detection. For each object, face is detected by using Haar-like feature and smoke is detected by reflecting frequency and direction of smoke in fast-motion foreground. Hand movements are detected by motion estimation. The algorithm examines the features in a certain interval and infers that whether the object is a smoker. It robustly can detect a smoker among different objects while achieving real-time performance.

• KIISE Transactions on Computing Practices
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• v.21 no.7
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• pp.494-499
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• 2015

As the size of data increases, it becomes important to identify properties by analyzing big data. In this paper, we propose a k-Means based efficient clustering technique, called MCSKMeans (Multi centroid set k-Means), using distributed parallel processing framework MapReduce. A problem with the k-Means algorithm is that the accuracy of clustering depends on initial centroids created randomly. To alleviate this problem, the MCSK-Means algorithm reduces the dependency of initial centroids using sets consisting of k centroids. In addition, we apply the agglomerative hierarchical clustering technique for creating k centroids from centroids in m centroid sets which are the results of the clustering phase. In this paper, we implemented our MCSK-Means based on the MapReduce framework for processing big data efficiently.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.996-1001
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• 2010

In this paper, network selection algorithm for services of mobile IPTV(internet protocol television) and implementation of a hierarchical processing system for reducing overload by terminal with low speed is proposed. This algorithm selects the network according to the following priorities derived from formulas; value that uses remaining bandwidth, network cost, signal strength. If terminal has a low processing power for using selected network and TV service, quality of service declines due to the system overloading. Hence, we implemented system which processes selected network and TV services accomplished by layer divided. Through experiments results, the method of direct user network selection waits for bandwidth assignment. However, on the one hand, that waiting time in exhausted situation will be very long. On the other hand, if we consider the priority plot of used networks, we should select the network with the best state. Therefore, data transmission rate will keep on average and the waiting time will be low.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1317-1341
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• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.117-125
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• 2022

Recently, as users' interest for travel increases, research on a travel route recommendation service that replaces the cumbersome task of planning a travel itinerary with automatic scheduling has been actively conducted. The most important and common goal of the itinerary recommendations is to provide the shortest route including popular tour spots near the travel destination. A number of existing studies focused on providing personalized travel schedules, where there was a problem that a survey was required when there were no travel route histories or SNS reviews of users. In addition, implementation issues that need to be considered when calculating the shortest path were not clearly pointed out. Regarding this, this paper presents a quantified method to find out popular tourist destinations using social big data, and discusses problems that may occur when applying the shortest path algorithm and a heuristic algorithm to solve it. To verify the proposed method, 63,000 places information was collected from the Gyeongnam province and big data analysis was performed for the places, and it was confirmed through experiments that the proposed heuristic scheduling algorithm can provide a timely response over the real data.