• International journal of advanced smart convergence
• /
• v.11 no.3
• /
• pp.1-6
• /
• 2022

In this paper, we estimate the mean number of objects in the M/H₂/1 model for web service when the mean object size in the M/H₂/1 model is equal to that of the M/G/1/PS and M/BP/1 models. To this end, we use the mean object size obtained by assuming that the mean latency of deterministic model is equal to that of M/H₂/1, M/G/1/PS, and M/BP/1 models, respectively. Computational experiments show that if the shape parameter of the M/BP/1 model is 1.1 and the system load is greater than 0.35, the mean number of objects in the M/H₂/1 model when mean object size of M/H₂/1 model is the same as that of M/G/1/PS model is almost equal to the mean number of objects in the M/H₂/1 model when the mean object size of M/H₂/1 model is the same as that of M/BP/1 model. In addition, as the upper limit of the M/BP/1 model increases, the number of objects in the M/H₂/1 model converges to one, which increases latency. These results mean that it is efficient to use small-sized objects in the web service environment.

• Journal of Information Processing Systems
• /
• v.10 no.2
• /
• pp.271-282
• /
• 2014

The advancement of knowledge society has enabled the social network community (SNC) to be perceived as another space for learning where individuals produce, share, and apply content in self-directed ways. The content generated within social networks provides information of value for the participants in real time. Thus, this study proposes the social network community activity-based content model (SoACo Model), which takes SNC-based activities and embodies them within learning objects. The SoACo Model consists of content objects, aggregation levels, and information models. Content objects are composed of relationship-building elements, including real-time, changeable activities such as making friends, and participation-activity elements such as "Liking" specific content. Aggregation levels apply one of three granularity levels considering the reusability of elements: activity assets, real-time, changeable learning objects, and content. The SoACo Model is meaningful because it transforms SNC-based activities into learning objects for learning and teaching activities and applies to learning management systems since they organize activities -- such as tweets from Twitter -- depending on the teacher's intention.

• The KIPS Transactions:PartD
• /
• v.9D no.1
• /
• pp.43-56
• /
• 2002

Most of works have been performed on representation of spatiotemporal objects from various points of view. Most of them represent spatiotemporal objects using approaches from GIS, temporal databases, object-oriented databases or data type. Spatiotemporal objects can be classified as objects whose position and shape changes discretely over time, objects whose position changes continuously and objects whose shape changes continuously as well as position. Previous works on spatiotemporal model have focused on only one of them. In this paper, we propose a spatiotemporal model that can represent three types of objects in Euclidean plan. For this purpose, we represent both discrete and continuous moving objects by defining temporal model extended from valid time and by defining relationship between two consecutive versions of objects. The proposed spatiotemporal object model is based on open GIS specification so that it has compatibility with existing spatial data model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.05a
• /
• pp.633-637
• /
• 2001

In this paper, we proposed model creation algorithm for multiple moving objects tracking. The proposed algorithm is divided that the initial model creation step as moving objects are entered into background image and the model reformation step in the moving objects tracking step. In the initial model creation step, the initial model is created by AND operating division image, divided using difference image and clustering method, and edge image of the current image. In the model reformation step, a new model was reformed in the every frame to adapt appearance change of moving objects using Hausdorff Distance and 2D-Logarithmic searching algorithm. We simulated for driving cart in the road. In the result, model was created over 98% in case of irregular approach direction of cars and tracking objects number.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.44 no.1
• /
• pp.57-68
• /
• 2002

In the irrigation facilities, the irrigation system is connected systematically, and thus, it agrees to the object-oriented concept. Since it is necessary to go through comparative evaluations and to devise several alternatives plans in designing the irrigation system, it will be very efficient to use the objects that contain the design data. In this study, the object-oriented methodology has been proposed to define the objects, which will be used in the design system of irrigation facility. Furthermore, as for the essential elements of the objects, concept of element objects is formulated. By employing this concept, appropriate element objects have been derided for the irrigation facility. Necessary data model for realization of the objects is examined and selected. And then, required elements for applying the selected data model to the irrigation facility will be proposed

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.25 no.12
• /
• pp.1919-1925
• /
• 2001

Overhead cranes consist of trolley, girder, rope, objects, trolley motor, girder motor, and hoist motor. If objects are regarded as mass point, and the acceleration of hoisting motion for objects is neglected, analytical model of overhead cranes becomes a nonlinear model because the length of a rope changes. Equations of motion this model is derived of simultaneous differential equations fur motors and object. Positions of the model are controlled by optimal inputs which obtain from a nonlinear optimal control method. From the results of computer simulation, even if initial states of objects suing, it is founded that position of overhead cranes is controlled, and that swing of objects is suppressed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.8
• /
• pp.2688-2703
• /
• 2022

Research on the advanced detection of harmful objects in airport cargo for passenger safety against terrorism has increased recently. However, because associated studies are primarily focused on the detection of relatively large objects, research on the detection of small objects is lacking, and the detection performance for small objects has remained considerably low. Here, we verified the limitations of existing research on object detection and developed a new model called the Small Hazardous Object detection enhanced and reconstructed Model based on the You Only Look Once version 5 (YOLOv5) algorithm to overcome these limitations. We also examined the performance of the proposed model through different experiments based on YOLOv5, a recently launched object detection model. The detection performance of our model was found to be enhanced by 0.3 in terms of the mean average precision (mAP) index and 1.1 in terms of mAP (.5:.95) with respect to the YOLOv5 model. The proposed model is especially useful for the detection of small objects of different types in overlapping environments where objects of different sizes are densely packed. The contributions of the study are reconstructed layers for the Small Hazardous Object detection enhanced and reconstructed Model based on YOLOv5 and the non-requirement of data preprocessing for immediate industrial application without any performance degradation.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.11
• /
• pp.54-64
• /
• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has mainly analyzed with either unknown objects 2-dimensionally by vision sensor or known objects, such as cylindrical objects, 3-dimensionally. As extending the previous work, in this study we propose an algorithm to analyze grasp of unknown objects 3-dimensionally by using vision sensor. This is archived by two steps. The first step is to make a 3-dimensional geometrical model for unknown objects by using stereo matching. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand which has the characteristic of multi-finger hand and is easy to model. To find the optimal grasping points, genetic algorithm is employed and objective function minimizes the admissible force of finger tip applied to the objects. The algorithm is verified by computer simulation by which optimal grasping points of known objects with different angle are checked.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.1
• /
• pp.54-61
• /
• 2008

This paper proposes a new algorithm for detecting and recognizing overlapped objects among a stack of arbitrarily located objects using a signature representation scheme. The proposed algorithm consists of two processes of detecting overlap of objects and of determining the boundary between overlapping objects. To determine overlap of objects, in the first step, the edge image of object region is extracted and those areas in the object region are considered as the object areas if an area is surrounded by a closed edge. For each object, its signature image is constructed by measuring the distances of those edge points from the center of the object, along the angle axis, which are located at every angle with reference to the center of the object. When an object is not overlapped, its features which consist of the positions and angles of outstanding points in the signature are searched in the database to find its corresponding model. When an object is overlapped, its features are partially matched with those object models among which the best matching model is selected as the corresponding model. The boundary among the overlapping objects is determined by projecting the signature to the original image. The performance of the proposed algorithm has been tested with the task of picking the top or non-overlapped object from a stack of arbitrarily located objects. In the experiment, a recognition rate of 98% has been achieved.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.12 no.5
• /
• pp.415-427
• /
• 1987

This paper presents an experimental model-based vision system which can identify and locate objects in scenes containing multiple occluded parts. The objects are assumed to be rigid and planar parts. In any recognition system the-type of objects that might appear in the image dictates the type of knowledge that is needed to recognize the object. The data is reduced to a sequential list of points or pixels that appear on the boundary of the objects. Next the boundary of the objects is smoothed using a polygonal approximation algorithm. Recognition cosists in finding the prototype that matches model to image. Now the hidden edge is reconstructed by transition model objects into occluded objects. The best match is obtained by optimising some similarity measure.