• 한국경영정보학회:학술대회논문집
• /
• 한국경영정보학회 2007년도 International Conference
• /
• pp.551-556
• /
• 2007

This paper attempts to develop a framework for interrelationships among human resources information systems (HRIS), outsourcing, and corporate culture. This research investigates impacts of outsourcing HRIS on corporate culture. In this paper, we hypothesize that outsourcing corporate HRIS is less appealing (1) if the quality of product and customer service matters for a firm, (2) if a firm is concerned with a loss of intellectual property, and (3) if a firm requires maintenance of a distinctive human resource service function that is capable of meeting the challenges of fast changing customer demands in a dynamic business environment. In addition, this study argues companies must be aware of the total costs associated with HRIS before outsourcing its human resource functions. Finally, the impact on employee morale and performance must also be considered By outsourcing HRIS, managers will be able to spend more time and resources dedicated to an employee's professional career development.

• 한국정보통신학회논문지
• /
• 제24권10호
• /
• pp.1398-1401
• /
• 2020

We present the concept of a Medical Digital Twin (MDT) that can predict and analyze medical diseases using computer simulations and introduce a dynamic virtual body capture system to create it. The MDT is a technology that creates a 3D digital virtual human body by reflecting individual medical and biometric information. The virtual human body is composed of a static virtual human body that reflects an individual's internal and external information and a dynamic virtual human body that reflects his motion. Especially we describe an early version of the dynamic virtual body capture system that enables continuous simulation of musculoskeletal diseases.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제7권11호
• /
• pp.2839-2852
• /
• 2013

Context-awareness is an essential part of ubiquitous computing, and over the past decade video based activity recognition (VAR) has emerged as an important component to identify user's context for automatic service delivery in context-aware applications. The accuracy of VAR significantly depends on the performance of the employed human body segmentation algorithm. Previous human body segmentation algorithms often engage modeling of the human body that normally requires bulky amount of training data and cannot competently handle changes over time. Recently, active contours have emerged as a successful segmentation technique in still images. In this paper, an active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR. The proposed technique not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise. Moreover, it is unsupervised, i.e., no prior human body model is needed. The performance of the proposed segmentation technique is compared against conventional CV Active Contour (AC) model using a depth-camera and obtained much better performance over it.

• 인터넷정보학회지
• /
• 제14권3호
• /
• pp.52-57
• /
• 2013

Information and Communication Technologies(ICTs) have substantially enlarged both the opportunities to realize one's human rights but have also resulted in the emergence of new challenges. ICTs are so deeply embedded and cental to almost all aspects of human activity. And ICTs are assuming an increasingly central role in all aspects of human and societal development across the world. But this is especially true of the right to privacy, which faces challenges such as profiling and data mining for public(including national security) and private purposes. ICTs access is a fundamental right for all humans in the information age. So we have need for regulation based on human rights in the digital age. And governments have a responsibility to protect individuals against violations of human rights and data protection by public authorities, but also by private entities. In addition, internet governance and multi-stakeholder principle have to be stressed on all of the internet issues because internet governance is included in the principle of democracy which have bottom-up communication and equality. So it is very importance that Internet Governance Forum is the space for a meaningful discussion on public policy issues relating to the internet.

• Transactions on Control, Automation and Systems Engineering
• /
• 제3권1호
• /
• pp.10-14
• /
• 2001

We studied the use of time-related information, with and without prediction, to support human operators performing moni-toring and control tasks in the process. Based on monitoring and control techniques used for Project Management we developed a display design for the process industries. A simulated power plant was used to test the hypothesis that availability of predictions along with information on past trends can improve the performances of the human operator handling faults. Several designs of dis-plays were tested in the experiment in which human operators had to detect and handle two types of faults(local and systems wide) in the simulated electricity generation process. Analysis of the results revealed that temporal data, with and without prediction, signifi-cantly reduced response time. Our results encourage the integration of temporal information and prediction in displays used for the control processes to enhance the capabilities of the human operators. Based on the analysis we proposed some guidelines for the de-signer of the human interface of a process control system.

• 한국멀티미디어학회논문지
• /
• 제23권12호
• /
• pp.1540-1551
• /
• 2020

Aiming at the problem that the existing human behavior recognition algorithm cannot fully utilize the multi-level spatio-temporal information of the network, a human behavior recognition algorithm based on a dense three-dimensional residual network is proposed. First, the proposed algorithm uses a dense block of three-dimensional residuals as the basic module of the network. The module extracts the hierarchical features of human behavior through densely connected convolutional layers; Secondly, the local feature aggregation adaptive method is used to learn the local dense features of human behavior; Then, the residual connection module is applied to promote the flow of feature information and reduced the difficulty of training; Finally, the multi-layer local feature extraction of the network is realized by cascading multiple three-dimensional residual dense blocks, and use the global feature aggregation adaptive method to learn the features of all network layers to realize human behavior recognition. A large number of experimental results on benchmark datasets KTH show that the recognition rate (top-l accuracy) of the proposed algorithm reaches 93.52%. Compared with the three-dimensional convolutional neural network (C3D) algorithm, it has improved by 3.93 percentage points. The proposed algorithm framework has good robustness and transfer learning ability, and can effectively handle a variety of video behavior recognition tasks.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
• /
• 한국정보과학회언어공학연구회 2002년도 제14회 한글 및 한국어 정보처리 학술대회
• /
• pp.325-331
• /
• 2002

정보추출 시스템의 목적은 관심의 대상이 되는 특정 정보를 선택적으로 찾아내 제시하는데 있다. 따라서 도메인 정보에 의존적인 방법으로 정보추출이 이루어질 수밖에 없고, 이에 따른 도메인 정보 구축의 부담이 컸다. 이러한 부담을 줄이기 위해 본 연구에서는 특정 주제영역과 관련한 문서로부터 자동으로 이벤트 문장을 추출하는 시스템을 제안한다. 이벤트 문장이란, 특정도메인에서 다루어지는 이벤트의 구체적인 내용을 포함하고 있는 문장이다. 이러한 문장을 추출함으로써 기본적인 수준의 정보추출 요구를 만족시킬 수 있을 뿐만 아니라, 주출된 이벤트 문장을 도메인 정보 구축에 활용할 수 있을 것이다. 본 연구에서는 동사, 명사, 명사구, 및 3W 자질을 이용하여 문장추출의 성능을 최대화하기 위한 방안을 제안하고, 세 개의 평가 도메인을 대상으로 실험을 수행하였다. 실험 결과, when 및 where 자질과 동사, 명사. 명사구의 가중치를 이용하여 문장 가중치를 계산함으로써 최적의 이벤트 문장추출 성능을 얻을 수 있음을 알 수 있었다.

• 대한원격탐사학회지
• /
• 제17권4호
• /
• pp.319-334
• /
• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권6호
• /
• pp.3182-3198
• /
• 2019

Vision-based Human Pose Estimation has been considered as one of challenging research subjects due to problems including confounding background clutter, diversity of human appearances and illumination changes in scenes. To tackle these problems, we propose to use a new multi-stage convolution machine for estimating human pose. To provide better heatmap prediction of body joints, the proposed machine repeatedly produces multiple predictions according to stages with receptive field large enough for learning the long-range spatial relationship. And stages are composed of various modules according to their strategic purposes. Pyramid stacking module and dilation module are used to handle problem of human pose at multiple scales. Their multi-scale information from different receptive fields are fused with concatenation, which can catch more contextual information from different features. And spatial and channel information of a given input are converted to gating factors by squeezing the feature maps to a single numeric value based on its importance in order to give each of the network channels different weights. Compared with other ConvNet-based architectures, we demonstrated that our proposed architecture achieved higher accuracy on experiments using standard benchmarks of LSP and MPII pose datasets.

• 한국컴퓨터정보학회논문지
• /
• 제16권1호
• /
• pp.201-210
• /
• 2011

정보기술의 발전은 사회의 각 영역에 많은 변화를 가져왔다. 특히 네트워크 기술을 기반으로 등장한 NCW(Network Centric Warfare)는 현대전 수행을 위한 새로운 패러다임이 되었다. 또한 NCW 구현의 핵심체계하고 할 수 있는 C4I 체계 구축을 통해 NCW 효과를 극대화 할 수 있게 되었다. 그러나 C4I체계는 인간이 가진 지식과 역량이 주도하는 것으로 인간차원의 영향력을 배제한다면, 그 효과를 기대할 수 없을 것이다. 본 논문에서는 C4I체계를 중심으로 기존의 연구방법에서 간과하였던 인적요소의 영향력을 반영하여 전투효과를 평가하는 알고리즘을 제안한다. 기존의 연구와 비교 평가한 결과, 제안한 알고리즘이 보다 현실에 부합하는 것으로 확인하였다. 또한 전투에 있어서 인적요소(협업)의 영향력이 무엇보다 중요함을 증명하였다. 따라서 제안하는 알고리즘은 전투효과 뿐만 아니라, 일반 기업의 임무효과 및 인적자원의 효율적 관리에 유용하게 활용될 수 있을 것이다.