• Journal of the Korean Institute of Intelligent Systems
• /
• v.27 no.2
• /
• pp.126-131
• /
• 2017

In this paper, we propose a method to extract meaningful motion among various kinds of hand gestures on giving commands to robots using hand gestures. On giving a command to the robot, the hand gestures of people can be divided into a preparation one, a main one, and a finishing one. The main motion is a meaningful one for transmitting a command to the robot in this process, and the other operation is a meaningless auxiliary operation to do the main motion. Therefore, it is necessary to extract only the main motion from the continuous hand gestures. In addition, people can move their hands unconsciously. These actions must also be judged by the robot with meaningless ones. In this study, we extract human skeleton data from a depth image obtained by using a Kinect v2 sensor and extract location data of hands data from them. By using the Kalman filter, we track the location of the hand and distinguish whether hand motion is meaningful or meaningless to recognize the hand gesture by using the hidden markov model.

• Research in Community and Public Health Nursing
• /
• v.7 no.2
• /
• pp.183-202
• /
• 1996

This study was designed out to develop a home health care service for nurses working in community care services. This study investigates actual conditions at welfare institutions related to health needs the demands of clients, and the state of home health care services we hope that this study will improve upon the current service system. In Korea home health care services are still developing and only new becoming a part of the health care supply system. The data was collected by recording the client home nursing assessments modified to the situation of UTMB home health agency. In this study 107 clients were selected for home care who needed care for physical and mental deficits. The study lasted from March to November of 1995 at one of the welfare service institutions in Chunchon city. The results show that those who most frequently needed care services were over 50 years old with a health deficit of 80.3%, followed by sex as women who needed care at 59.8%. 50.5% of the clients had very little education. 99.1% of the clients live with their family, and a medical diagnostic analysis reveals that 73.9% of the 5 year period of illnesses were the following : 38.8% - muscular -skeleton system disorder, 24.4% - hypertension and stroke, 25.7% sole disease of arthritis. For behavioral conditions 43.3% of the patients were without care services, 56.6% of the patients were taking treatment that 73.5% of those were taking medication. The most main complaint of patients were 22.4% of pain in the extremities, next were 16.8% of a limitation of body activities, 15.0% was lumbo-sacralgia. According to the investigator who was a senior student nurse, the following suggestions were made: 32.7% for curative medical services, 29.9% for physical exercise, 19.6% for emotional support. Consultation nursing services consisted of 67.2% for physical therapy, 11.2% for the maintaining healing, 9.4% for counseling. The patients at home, required assistance most frequently for muscular-skeleton problems under the category of physical systems (33.3%). But, on the other hand, 49.5% of the patients required care givers at home, 28.2% had a knowledge deficit, 21.0% had malnutrition, 18.4% had bad impaired communication. The character of health problems were devided into chronic disease(67.0%), accidents(I3.1%), and general disease(15.9%). 86% of the disabled client had an impairment of the physical system. Eating (86.9%) , Toileting(77.6%), and personal care showed much the same of ADL condition, the level and range of achievement of mobility, the most frequently self performed was 81.3% only in a room size area, and 40.2% were completely dependent when going out. Although there were a large number of home care services in th community at these welfare institutions, many clients needed a variety of curative services. As policy changes have gathered momentum, responsibility for the development of a more suitable program was demanded by the clients from the community.

• Journal of KIISE:Computing Practices and Letters
• /
• v.6 no.2
• /
• pp.120-134
• /
• 2000

In this paper we present a Distributed Object oriented Virtual computing Environment, called DOVE which consists of autonomous distributed objects interacting with one another via method invocations based on a distributed object model. DOVE appears to a user logically as a single virtual computer for a set of heterogeneous hosts connected by a network as if objects in remote site reside in one virtual computer. By supporting efficient parallelism, heterogeneity, group communication, single global name service and fault-tolerance, it provides a transparent and easy-to-use programming environment for parallel applications. Efficient parallelism is supported by diverse remote method invocation, multiple method invocation for object group, multi-threaded architecture and synchronization schemes. Heterogeneity is achieved by automatic data arshalling and unmarshalling, and an easy-to-use and transparent programming environment is provided by stub and skeleton objects generated by DOVE IDL compiler, object life control and naming service of object manager. Autonomy of distributed objects, multi-layered architecture and decentralized approaches in hierarchical naming service and object management make DOVE more extensible and scalable. Also,fault tolerance is provided by fault detection in object using a timeout mechanism, and fault notification using asynchronous exception handling methods

• Journal of the Korea Computer Graphics Society
• /
• v.28 no.2
• /
• pp.1-9
• /
• 2022

In this paper, we propose a vector-based augmentation technique that can generate data required for crack detection and a ConvNet(Convolutional Neural Network) technique that can learn it. Detecting cracks quickly and accurately is an important technology to prevent building collapse and fall accidents in advance. In order to solve this problem with artificial intelligence, it is essential to obtain a large amount of data, but it is difficult to obtain a large amount of crack data because the situation for obtaining an actual crack image is mostly dangerous. This problem of database construction can be alleviated with elastic distortion, which increases the amount of data by applying deformation to a specific artificial part. In this paper, the improved crack pattern results are modeled using ConvNet. Rather than elastic distortion, our method can obtain results similar to the actual crack pattern. By designing the crack data augmentation based on a vector, rather than the pixel unit used in general data augmentation, excellent results can be obtained in terms of the amount of crack change. As a result, in this paper, even though a small number of crack data were used as input, a crack database can be efficiently constructed by generating various crack directions and patterns.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.7
• /
• pp.479-486
• /
• 2013

The data model that can be said as skeleton of the information system constitutes important 2 axles in the information system together with the process model. There is entity, properties, relation as key factors of the data model, and entity is the most fundamental factor in the data model, and thus total data model becomes vague if not deriving entity definitely. This study dealt with entity deduction only. Deducing methods of existing entity depended on experiences, task knowledge of designers and clear procedures were not suggested, so there were many difficulties in approaching them from beginners or unskilled persons. For giving helps in solving the problem, this study proposes entity- deducing procedures based on tasks that can derive entity with a systematic process at previously derived target businesses through suggested methods from advancing researches. And the study enabled proposing procedures on imaginary tasks to be applied, objecting to undergraduates who had not experiences on the data modeling, and then verified suggesting process through a similarity checking between best answers with deduced entity by students after taking impossible points of comparing existing methods with suggesting process into consideration. By doing so, deducing entity closely to the best answer was confirmed accordingly. Therefore, a fact could be confirmed that beginners were able to deduce entity closely to the best answer even if letting beginners who had not experiences on the data modeling be applied to unfamiliar tasks. Regarding researches on properties and relation deduction besides entity, this study leaves them to next time.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.9
• /
• pp.53-62
• /
• 2020

Product recommendation services that have been researched recently are only recommended through the customer's product purchase history. In this paper, we propose the digital signage service through customers' behavior pattern analysis that is recommending through not only purchase history, but also behavior pattern that customers take when choosing products. This service analyzes customer behavior patterns and extracts interests about products that are of practical interest. The service is learning extracted interest rate and customers' purchase history through the Wide & Deep model. Based on this learning method, the sparse vector of other products is predicted through the MF(Matrix Factorization). After derive the ranking of predicted product interest rate, this service uses the indoor signage that can interact with customers to expose the suitable advertisements. Through this proposed service, not only online, but also in an offline environment, it would be possible to grasp customers' interest information. Also, it will create a satisfactory purchasing environment by providing suitable advertisements to customers, not advertisements that advertisers randomly expose.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.38 no.10
• /
• pp.1139-1145
• /
• 2014

Creation of a human skeleton model and characterization of the variation in the bone shape are fundamentally important in many applications of biomechanics. In this paper, we present a parametric shape modeling method for femurs that is based on extracting the main parameter of variations of the femur shape from a 3D model database by using statistical shape analysis. For this shape analysis, principal component analysis (PCA) is used. Application of the PCA to 3D data requires bringing all the models in correspondence to each other. For this reason, anatomical landmarks are used for guiding the deformation of the template model to fit the 3D model data. After subsequent application of PCA to a set of femur models, we calculate the correlation between the dominant components of shape variability for a target population and the anatomical parameters of the femur shape. Finally, we provide tools for visualizing and creating the femur shape using the main parameter of femur shape variation.

• Journal of KIISE:Software and Applications
• /
• v.30 no.1_2
• /
• pp.103-116
• /
• 2003

States explosion due to composition of spaces of data, temporal, and locational values is one of the well-known critical problems which cause difficulty in understanding and analysing real-time systems specified with state-based formal methods. In order to overcome this problem, this paper presents an abstraction method for state minimization based on an abstraction in system specification and an abstraction in system execution. The first is named the syntactic in system specification and an abstraction in system execution. The first is named the syntactic abstraction, through which the patterns of the unconditionally internalized computation and the repetition and selection structures are abstracted. The latter is named the semantic abstraction, through which the patterns of the execution space represented with data. Through the abstractions, the components of a system in specification and execution model is hierarchically organized. The system can be analyzed briefly in the upper level in an skeleton manner with low complexity. The system, however, can be abstraction method for the state minimization and the decrease in analysis complexity through the abstraction with examples.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.5
• /
• pp.53-60
• /
• 2013

This paper proposed visualization tool for motion of snowboarding using Skeleton data obtained by the Microsoft's Kinect sensor. The BBP(Balanced Body Position) posture is a most basic motion in the Snowboarding. This posture is the primary technology for stable turns. The implementation of visualization tool to analyse the BBP posture of snowboard. comparative analysis with standard postures to the ankles, knees, hips and spine angle of joints and body tracking using coordinate information obtained by the Kinect Sensor. Analysis of the final results of the screen through the OpenGL library. This research result could be used to analysis for turn postures of snowboarding.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.6
• /
• pp.718-723
• /
• 2011

In this paper, we propose a visual multi-touch air input device using vision cameras. The implemented device provides a barehanded interface which copes with the multi-touch operation. The proposed device is easy to apply to the real-time systems because of its low computational load and is cheaper than the existing methods using glove data or 3-dimensional data because any additional equipment is not required. To do this, first, we propose an image processing algorithm based on the HSV color model and the labeling from obtained images. Also, to improve the accuracy of the recognition of hand gestures, we propose a motion recognition algorithm based on the geometric feature points, the skeleton model, and the Kalman filter. Finally, the experiments show that the proposed device is applicable to remote controllers for video games, smart TVs and any computer applications.