• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.10
• /
• pp.4025-4041
• /
• 2020

Mobile edge computing (MEC) is capable of providing services to smart devices nearby through radio access networks and thus improving service experience of users. In this paper, an offloading strategy for the joint optimization of computing and communication resources in multi-user and multi-MEC overlapping scene was proposed. In addition, under the condition that wireless transmission resources and MEC computing resources were limited and task completion delay was within the maximum tolerance time, the optimization problem of minimizing energy consumption of all users was created, which was then further divided into two subproblems, i.e. offloading strategy and resource allocation. These two subproblems were then solved by the game theory and Lagrangian function to obtain the optimal task offloading strategy and resource allocation plan, and the Nash equilibrium of user offloading strategy games and convex optimization of resource allocation were proved. The simulation results showed that the proposed algorithm could effectively reduce the energy consumption of users.

• Journal of Information Processing Systems
• /
• v.8 no.2
• /
• pp.331-346
• /
• 2012

Task-based programming is becoming the state-of-the-art method of choice for extracting the desired performance from multi-core chips. It expresses a program in terms of lightweight logical tasks rather than heavyweight threads. Intel Threading Building Blocks (TBB) is a task-based parallel programming paradigm for multi-core processors. The performance gain of this paradigm depends to a great extent on the efficiency of its parallel constructs. The parallel overheads incurred by parallel constructs determine the ability for creating large-scale parallel programs, especially in the case of fine-grain parallelism. This paper presents a study of TBB parallelization overheads. For this purpose, a TBB micro-benchmarks suite called TBBench has been developed. We use TBBench to evaluate the parallelization overheads of TBB on different multi-core machines and different compilers. We report in detail in this paper on the relative overheads and analyze the running results.

• Design & Manufacturing
• /
• v.17 no.4
• /
• pp.57-62
• /
• 2023

As a representative method for mass production, a multi-cavity type mold capable of simultaneously molding products of the same shape can be applied. It has the advantage of improving the productivity from several times to several tens of times, but it may cause disadvantages which is the quality deviation with each cavity. This study, therefore, has tried to increase the cavity filling balance by using a melt flipper and a flow distance control part in the runner part of the mold. Along with this, the design and manufacturing of air vents during injection molding have been verified through experimental methods to achieve a higher level of multi-cavity filling balance and dimensional accuracy.

• Korean Journal of Applied Biomechanics
• /
• v.29 no.3
• /
• pp.157-166
• /
• 2019

Objective: This study examined the effects of stimulating fingertip temperature on the patterns of force sharing and stability properties during multi-finger force production tasks. Method: 9 adult subjects (male: 3, female: 6, age: $26.11{\pm}4.01yrs$, height: $169.22{\pm}5.97cm$, weight: $61.44{\pm}11.27kg$) participated in this study. The experiment consisted of three blocks: 1) maximal voluntary contraction (MVC) task, 2) single-finger ramp task to quantify enslaving (i.e., unintended force production by non-task fingers), and 3) 12 trials of multi-finger steady-state force production task at 20% MVC. There were three temperature conditions including body-temperature (i.e., control condition), $40^{\circ}C$, and $43^{\circ}C$, and the stimulation was given to the index finger only for all experimental conditions. Results: There were no significant differences in the MVC forces, enslaving, and the accuracy of performance during the steady-state task between the conditions. However, the share of stimulated index finger force increased with the index fingertip temperature, while the share of middle finger force decreased. Also, the coefficient of variation of both index and middle finger forces over repetitive trials increased with the index fingertip temperature. Under the framework of the uncontrolled manifold (UCM) hypothesis used to quantify indices of multi-finger synergies (i.e., stability property) stabilizing total force during the steady-state task, the two variance components within the UCM analysis increased together with the fingertip temperature, while no changes in the synergy indices between the conditions. Conclusion: The current results showed that fingertip temperature stimulation only to index finger does not affect to muscle force production capability of multi-finger, independence of individual fingers, and force production accuracy by the involvement of all four fingers. The effect of fingertip temperature on the sharing pattern and force variation may be due to diffuse reflex effects of the induced afferent activity on alpha-motoneuronal pools. However, the unchanged stability properties may be the reflection of the active error compensation strategies by non-stimulated finger actions.

• Journal of Broadcast Engineering
• /
• v.27 no.3
• /
• pp.273-282
• /
• 2022

MPEG-VCM(Video Coding for Machine) aims to standardize video codec for machines. VCM provides data sets and anchors, which provide reference data for comparison, for several machine vision tasks including object detection, object segmentation, and object tracking. The evaluation template can be used to compare compression and machine vision task performance between anchor data and various proposed video codecs. However, performance comparison is carried out separately for each machine vision task, and information related to performance evaluation of multiple machine vision tasks on a single bitstream is not provided currently. In this paper, we propose a performance evaluation method of a video codec for AI-based multi-tasks. Based on bits per pixel (BPP), which is the measure of a single bitstream size, and mean average precision(mAP), which is the accuracy measure of each task, we define three criteria for multi-task performance evaluation such as arithmetic average, weighted average, and harmonic average, and to calculate the multi-tasks performance results based on the mAP values. In addition, as the dynamic range of mAP may very different from task to task, performance results for multi-tasks are calculated and evaluated based on the normalized mAP in order to prevent a problem that would be happened because of the dynamic range.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.2
• /
• pp.483-503
• /
• 2014

In this paper, human action recognition using pyramid histograms of oriented gradients and collaborative multi-task learning is proposed. First, we accumulate global activities and construct motion history image (MHI) for both RGB and depth channels respectively to encode the dynamics of one action in different modalities, and then different action descriptors are extracted from depth and RGB MHI to represent global textual and structural characteristics of these actions. Specially, average value in hierarchical block, GIST and pyramid histograms of oriented gradients descriptors are employed to represent human motion. To demonstrate the superiority of the proposed method, we evaluate them by KNN, SVM with linear and RBF kernels, SRC and CRC models on DHA dataset, the well-known dataset for human action recognition. Large scale experimental results show our descriptors are robust, stable and efficient, and outperform the state-of-the-art methods. In addition, we investigate the performance of our descriptors further by combining these descriptors on DHA dataset, and observe that the performances of combined descriptors are much better than just using only sole descriptor. With multimodal features, we also propose a collaborative multi-task learning method for model learning and inference based on transfer learning theory. The main contributions lie in four aspects: 1) the proposed encoding the scheme can filter the stationary part of human body and reduce noise interference; 2) different kind of features and models are assessed, and the neighbor gradients information and pyramid layers are very helpful for representing these actions; 3) The proposed model can fuse the features from different modalities regardless of the sensor types, the ranges of the value, and the dimensions of different features; 4) The latent common knowledge among different modalities can be discovered by transfer learning to boost the performance.

• Journal of Digital Convergence
• /
• v.17 no.12
• /
• pp.243-248
• /
• 2019

Multi-Task Learning(MTL) is a training method that trains a single neural network with multiple tasks influences each other. In this paper, we compare performance of MTL Named entity recognition(NER) model trained with Korean traditional culture corpus and other NER model. In training process, each Bi-LSTM layer of Part of speech tagging(POS-tagging) and NER are propagated from a Bi-LSTM layer to obtain the joint loss. As a result, the MTL based Bi-LSTM model shows 1.1%~4.6% performance improvement compared to single Bi-LSTM models.

• Journal of KIISE:Software and Applications
• /
• v.27 no.8
• /
• pp.834-845
• /
• 2000

Most agents are associated with plan rules for their tasks when they are created. In a multi-agent system in which many agents are interacting, the direct use of predefined plan rules of each agents may slow down the system due to the lack of recognition of the relationship among plan rules of the agents. In order to overcome this, we need to analyze and integrate the agent's plan rules to facilitate concurrent rule execution. This paper proposes a method that integrates and executes local plan rules of task agents in a multi-agent environment. The results of the integration are represented in a network structure. For domain task execution, a task agent collects other task agents' plan rules and builds an integrated domain network, which is exploited to achieve the goal. The agent problem solving by using the domain network enables not only the concurrent plan execution but the solution of coordination problems.

• Journal of Korea Society of Industrial Information Systems
• /
• v.26 no.5
• /
• pp.11-19
• /
• 2021

In this paper, we proposed an asymmetric multi-core processor scheduling scheme which is based on the mileage of each core. We considered a big-LITTLE multi-core processor structure, which consists of low power consuming LITTLE cores with general performance and high power consuming big cores with high performance. If a task needs to be processed, the processor decides a core type (big or LITTLE) to handle the task, and then investigate the core with the shortest mileage among unoccupied cores. Then assigns the task to the core. We developed a mileage-based balancing algorithm for asymmetric multi-core assignment and showed that the proposed scheduling scheme is more cost-effective compared to the traditional scheme from a management perspective. Simulation is also conducted for the purpose of performance evaluation of our proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.180-185
• /
• 2003

In order to enhance dexterity in execution of robot tasks, a redundant number of degrees-of-freedom (DOF) is adopted for design of robotic mechanisms like robot arms and multi-fingered robot hands. Associated with such redundancy in the number of DOFs relative to the number of physical variables necessary and sufficient for description of a given task, an extra performance index is introduced for controlling such a redundant robot in order to avoid arising of an ill-posed problem of inverse kinematics from the task space to the joint space. This paper shows that such an ill-posedness of DOF redundancy can be resolved in a natural way by using a novel concept named “stability on a manifold”. To show this, two illustrative robot tasks 1) robotic handwriting and 2) control of an object posture via rolling contact by a multi-DOF finger are analyzed in details.