• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• Journal of Audiology & Otology
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• v.24 no.1
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• pp.29-34
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• 2020

Background and Objectives: Bilateral microphones with contralateral routing of signal (BiCROS) hearing aid is an option for hearing rehabilitation in individuals with asymmetric sensorineural hearing loss (ASNHL). The clinical factors influencing the trial and purchase of BiCROS were investigated. Subjects and Methods: We reviewed the medical records of 78 patients with ASNHL who were recommended to use BiCROS and analyzed the demographic and audiological factors influencing the trial and purchase of BiCROS. Results: Among the 78 patients, 52 (66.7%) availed of the free BiCROS trial and 21 (26.9%) purchased BiCROS. The mean pure tone audiometry (PTA) air conduction (AC) threshold of the better- and worse-hearing ears were 44.2±12.8 dB and 90.7±22.5 dB HL, respectively. The decision for trial or purchase of BiCROS was not influenced by age, sex, duration of hearing loss of the worse-hearing ear, or PTA AC threshold or speech discrimination score of both ears. The first and third quartiles of the PTA AC thresholds for the better-hearing ear of BiCROS buyers were 38.75 dB and 53.75 dB HL, respectively. The counterpart values for the worse-hearing ear were 72.50 dB and 118.75 dB HL, respectively. Conclusions: The clinical factors analyzed in this study were found to be irrelevant to the trial and purchase of BiCROS in patients with ASNHL. Nevertheless, the distribution range of the auditory thresholds of the subjects using BiCROS can be a useful basis for the counseling of patients with ASNHL and selection of candidates for BiCROS use.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.58-63
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• 2017

Emergencies and disasters can happen any time without any warning, and things can change and escalate very quickly, and often it is swift and decisive actions that make all the difference. It is a responsibility of the building facility management to ensure that a proven evacuation plan in place to cover various worst scenario to handled automatically inside the facility. To mapping out optimal safe escape routes is a straightforward undertaking, but does not necessarily guarantee residents the highest level of protection. The emergency evacuation navigation approach is a state-of-the-art that designed to evacuate human livings during an emergencies based on real-time decisions using live sensory data with pre-defined optimum path finding algorithm. The poor decision on causalities and guidance may apparently end the evacuation process and cannot then be remedied. This paper propose a cloud connected emergency evacuation system model to react dynamically to changes in the environment in emergency for safest emergency evacuation using IoT based emergency exit sign system. In the previous researches shows that the performance of optimal routing algorithms for evacuation purposes are more sensitive to the initial distribution of evacuees, the occupancy levels, and the type and level of emergency situations. The heuristic-based evacuees routing algorithms have a problem with the choice of certain parameters which causes evacuation process in real-time. Therefore, this paper proposes an evacuee routing algorithm that optimizes evacuation by making using high computational power of cloud servers. The proposed algorithm is evaluated via a cloud-based simulator with different "simulated casualties" are then re-routed using a Dijkstra's algorithm to obtain new safe emergency evacuation paths against guiding evacuees with a predetermined routing algorithm for them to emergency exits. The performance of proposed approach can be iterated as long as corrective action is still possible and give safe evacuation paths and dynamically configure the emergency exit signs to react for real-time instantaneous safe evacuation guidance.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.4
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• pp.51-63
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• 1994

Many themes have been studied for FMS problems. But most researches have focused on specific themes; Machine selection, Loading, Routing, Machine layout, etc. So many decision makers who want to introduce FMS to his factory, have many problems, because they do not know either what size of FMS should be introduced or what amount of money should be invested. The objective of this research is to help the decision makers who want to introduce FMS. This research consists of three major part, first, Machine selection, second, Loading, and third, Machine Layout. In the first part of the research, machines are selected with minimum cost satisfying the given demand of each part. In the second part, each operations with its required tools are allocated to those machines. In the third part the locations of each selected machines are determined. And dissimilarity coefficients between each pair of machines are calculated as the measure of distance. With above three steps, we have selected machines, allocated operations to those machines, and the layout configuration of those machines. And for each three steps, Mixed Integer Programming models are formulated. In order to solve the large problems and reduce the computer execution time, three heuristic algorithms are developed for the three mixed integer programming models.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.242-246
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• 2024

Automated route planning is an important tool in the field of built environment. For example, a high-quality route planning method can improve the logistics planning of projects, thereby enhancing the performance of projects and the effectiveness of management. However, the traditional automated route planning is performed based on the predicted mean value travel time of candidate routes. Such a point estimate neglects the purpose of the trip and can further lead to a suboptimal decision. Motivated by this challenge, this study proposes an innovative framework for trip purpose based route planning. The proposed artificial intelligence and stochastic optimization framework recommends the most appropriate travel route for decision makers by fully considering their trip requirements beyond just the shortest mean value travel time. In addition to its theoretical contributions, our proposed route planning method will also contribute to the current logistics planning practice. Future research may be devoted to the real-life implementation of the proposed methodology in a broader context to provide empirical insights for practitioners in various industries.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.81-91
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• 2005

The Traveling Salesman Problem(TSP) is one of the NP-complete (None-deterministic Polynomial time complete) route optimization problems. Its calculation time increases very rapidly as the number of nodes does. Therefore, the near optimum solution has been searched by heuristic algorithms rather than the real optimum has. This paper reviews the Ant System Algorithm(ANS), an heuristic algorithm of TSP and its applicability in the parcel delivery service in Korea. ASA, which is an heuristic algorithm of NP-complete has been studied by M. Dorigo in the early 1990. ASA finds the optimum route by the probabilistic method based on the cumulated pheromone on the links by ants. ASA has been known as one of the efficient heuristic algorithms in terms of its calculation time and result. Its applications have been expanded to vehicle routing problems, network management and highway alignment planning. The precise criteria for vehicle routing has not been set up in the parcel delivery service of Korea. Vehicle routing has been determined by the vehicle deriver himself or herself. In this paper the applicability of ASA to the parcel delivery service has been reviewed. When the driver s vehicle routing is assumed to follow the Nearest Neighbor Algorithm (NNA) with 20 nodes (pick-up and drop-off places) in $10Km{\times}10Km$ service area, his or her decision was compared with ASA's one. Also, ASA showed better results than NNA as the number of nodes increases from 10 to 200. If ASA is applied, the transport cost savings could be expected in the parcel delivery service in Korea.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.449-463
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• 2013

This study proposes the method for determining the Muskingum channel routing model parameters based on the assumption of linear system. The proposed method was applied to the Chungju dam basin for the evaluation. Additionally, the rainfall-runoff was repeated for the Yeongchun-Chungju dam reach using seven rainfall events observed. Summarizing the results is as follows. First, the concentration time and storage coefficient of a channel reach formed by the subdivision can be expressed as the difference between the concentration times and storage coefficients of upstream and downstream basins. The storage coefficients of the channel reach estimated is equal to the storage coefficient of the Muskingum channel routing model and the weight factor can be simply estimated using the ratio between the concentration time and storage coefficient. Second, the weight factor of the Muskingum model is in inverse proportion to the Russel coefficient, which is in between 0.4166 and 0.625 when considering the Russel coefficients generally applied. Finally the application to the Yeongchun-Chungju dam reach showed that the proposed method is still valid regardless of the limitations such as the uncertainty of the observed data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2620-2631
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• 2012

In this paper, a rerouting-controlled ISL (Inter-Satellite link) handover protocol for LEO satellite networks (RCIHP) is proposed. Through topological dynamics and periodic characterization of LEO satellite constellation, the protocol firstly derives the ISL related information such as the moments of ISL handovers and the intervals during which ISLs are closed and cannot be used to forward packet. The information, combined with satellite link load status, is then been utilized during packet forwarding process. The protocol makes a forwarding decision on a per packet basis and only routes packets to living and non-congested satellite links. Thus RCIHP avoids periodic rerouting that occurs in traditional routing protocols and makes it totally unnecessary. Simulation studies show that RCIHP has a good performance in terms of packet dropped possibility and end-to-end delay.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.478-478
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• 2000

In this paper, presents the design of mobile field robot controlled by microcomputer. The computer works as the supervisory system for decision making and sending command to control the field robot. An information from encoder, infrared sensors using for control task of the robot that can be interconnected with the computer through the serial communication RS422 standard. In this case, the user can design the program algorithm base on microcomputer in order to control and define the routing of the mobile robot. Moreover, the robot can be installed other equipment fer collect data such as picture, sound, temperature etc., in order to working in the dangerous area.

• IE interfaces
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• v.20 no.1
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• pp.58-68
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• 2007

This research deals with a vehicle scheduling problem for the sludge collection strategies which might be solved via quantitative analysis and cost evaluations schemes. This problem can be modeled as a kind of capacitated vehicle routing pick-up problems. With the aim of establishing operation schedule of vehicles and analyzing the total cost under considering various assumptions and realistic restrictions of the sludge collection problem, we propose a heuristic method based on the genetic algorithm in conjunction with the sweep algorithm and the 4-opt algorithm. Finally, we present the cost effective operation schedule that can be used as the managing tool for the sludge treatment plant of the multi-purpose dam.