• KIPS Transactions on Computer and Communication Systems
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• v.11 no.12
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• pp.437-444
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• 2022

Recently, research on mobile edge services has been conducted to handle computationally intensive and latency-sensitive tasks occurring in wireless networks. However, MEC, which is fixed on the ground, cannot flexibly cope with situations where task processing requests increase sharply, such as commuting time. To solve this problem, a technology that provides edge services using UAVs (Unmanned Aerial Vehicles) has emerged. Unlike ground MEC servers, UAVs have limited battery capacity, so it is necessary to optimize energy efficiency through load balancing between UAV MEC servers. Therefore, in this paper, we propose a load balancing technique with consideration of the energy state of UAVs and the mobility of vehicles. The proposed technique is composed of task offloading scheme using genetic algorithm and task migration scheme using Q-learning. To evaluate the performance of the proposed technique, experiments were conducted with varying mobility speed and number of vehicles, and performance was analyzed in terms of load variance, energy consumption, communication overhead, and delay constraint satisfaction rate.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.105-108
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• 2000

As Internet and WWW grow rapidly, the role of web servers is getting more important, and the number of users in a few popular site is also explosively increasing. Load balancing in clustered web server systems is important task to utilize whole system effectively, so dynamic load balancing is required to overcome the limit of static load balancing. In this paper, we propose two dynamic load balancing schemes, and analyzed load model and Performance improvement and also compare existing load balancing methods and IP filtering method. In case of load balancing with threshold, little extra traffic was required for better performance, but in case of load balancing with load weight, we found that the performance mainly depends on information exchange rate.

• International Journal of Contents
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• v.2 no.1
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• pp.39-44
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• 2006

Load sharing is a critical resource in computer system. In sender-initiated load sharing algorithms, the sender continues to send unnecessary request messages for load transfer until a receiver is found while the system load is heavy. Meanwhile, in the receiver initiated load sharing algorithms, the receiver continues to send an unnecessary request message for load acquisition until a sender is found while the system load is light. These unnecessary request messages result in inefficient communications, low CPU utilization, and low system throughput in distributed systems. To solve these problems, we propose a genetic algorithm based approach for improved sender-initiated and receiver-initiated load sharing in distributed systems. And we expand this algorithm to an adaptive load sharing algorithm. Compared with the conventional sender-initiated and receiver-initiated algorithms, the proposed algorithm decreases the response time and task processing time.

• Safety and Health at Work
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• v.8 no.1
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• pp.11-18
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• 2017

The purpose of this review is to name and describe the important factors of musculoskeletal strain originating from pushing and pulling tasks such as cart handling that are commonly found in industrial contexts. A literature database search was performed using the research platform Web of Science. For a study to be included in this review differences in measured or calculated strain had to be investigated with regard to: (1) cart weight/ load; (2) handle position and design; (3) exerted forces; (4) handling task (push and pull); or (5) task experience. Thirteen studies met the inclusion criteria and proved to be of adequate methodological quality by the standards of the Alberta Heritage Foundation for Medical Research. External load or cart weight proved to be the most influential factor of strain. The ideal handle positions ranged from hip to shoulder height and were dependent on the strain factor that was focused on as well as the handling task. Furthermore, task experience and subsequently handling technique were also key to reducing strain. Workplace settings that regularly involve pushing and pulling should be checked for potential improvements with regards to lower weight of the loaded handling device, handle design, and good practice guidelines to further reduce musculoskeletal disease prevalence.

• Educational Technology International
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• v.13 no.1
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• pp.79-100
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• 2012

The focus of this research is on identifying the problems that learners experience during online problem-based learning (e-PBL) from a cognitive perspective. The study is concentrated on learners' cognitive load level at each stage of e-PBL. The research questions are specifically as follows: What is the level of cognitive load at each stage of e-PBL and what is the relationship between cognitive load and group performance? What cognitive difficulties are experienced by learners in e-PBL and what causes cognitive difficulties? In this study, we found that cognitive load was the highest in stage 1 and there was negative relationship between cognitive load at stage 1 and group performance. In addition, learners experienced difficulties during e-PBL such as the complexity of task, the difficulty in collaboration, and the lack of appropriate references. For further study, we will investigate some strategies regarding adjusting learners' cognitive load in the early stages of e-PBL.

• Journal of Biosystems Engineering
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• v.38 no.2
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• pp.163-170
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• 2013

Purpose: The purpose of this study is to provide analysis of physiological, biomechanical responses occurring from the operation to lifting or twist lifting task appears frequently in agricultural work. Methods: This study investigated the changes of physiological factors such as heart rate, heart rate variability (HRV) and biomechanical factors such as physical activity and kinetic analysis in the task of twisting at the waist while lifting. Results: Heart rates changed significantly with the workload. The result indicated that the workload of 2 kg was light intensity work, and the workload of 12 kg was hard intensity work. Physical activity increased as the workload increased both on wrist and waist. Besides, stress index of the worker increased with the workload. Dynamic load to herniated discs was analyzed using inertial sensor, and the angular acceleration and torque increased with the workload. The proposed measurement system can measure the recipient's physiological and physical signals in real-time and analyzed 3-dimensionally according to the variety of work load. Conclusions: The system we propose will be a new method to measure agricultural workers' multi-dimensional signals and analyze various farming tasks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.1
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• pp.1-8
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• 2016

We proposed a load unbalancing scheduling method for energy-efficient multi-core embedded systems considering DVFS (Dynamic Voltage/Frequency Scaling) power consumption and task characteristics. It is a new kind of scheduler which combines load balancing and load unbalancing technique. The purpose of the method is to effectively utilize energy without much effect in performance. In this paper, we conduct experiments on energy consumption and performance using the previous load balancing and unbalancing techniques and our proposed technique. The proposed technique reduced energy consumption more than 13.7% when compared to other algorithms. As a result, the proposed technique shows low energy consumption without much decline in the performance and is adequate for energy-efficient multi-core embedded systems.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.197-202
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• 2001

The biomechanical analysis of the load carrying effect on different floor surfaces has been conducted. Four different floor surfaces were prepared for ten subjects with each walking at a fixed velocity(1.33 m/sec) while carrying five different loads. The results showed that because of the significant interaction effect between floor slipperiness and the load carrying task, the load carrying effect should be analyzed according to different levels of the floor slipperiness, especially contaminant floors. On oily surfaces, slip distance(SD) and heel velocity (HV) increased whereas stride length(SL) decreased as load increased. In other words, significantly longer SD, faster HV, and no normal gait were found as load increased. As a result, a different protocol should be applied to measure floor slipperiness on oily floors as compared to dry surfaces for tribological approach.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.103-108
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• 2005

Loading/Unloading task in the real industry is performed by crane, but most of the loading/unloading task with the weight of 5kg∼30kg is done by human workers and this kind of work causes industrial disaster of workers. Therefore it is necessary to develop low cost loading/unloading manipulator system to prevent this kind of industrial accidents. This paper is concerned with the design and fabrication of 2 axis pneumatic manipulators using on/off solenoid valves and accurate position control without respect to the external load and low damping in the pneumatic rotary actuator. To overcome the change of external load, switching of control parameter using LVQNN (Learning Vector Quantization Neural Network) is newly applied, which estimates the external loads in the pneumatic cylinder. As an underlying controller, a state feedback controller using position, velocity and acceleration is applied to the switching control system. The effectiveness of the proposed control algorithms are demonstrated through experiments of pneumatic cylinder with various loads.