• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.746-750
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• 2009

In this paper we focus on the Personal Space (PS) as a nonverbal communication concept to build a new Human Computer Interaction. The analysis of people positions with respect to their PS gives an idea on the nature of their relationship. We propose to analyze and model the PS using Computer Vision (CV), and visualize it using Computer Graphics. For this purpose, we define the PS based on four parameters: distance between people, their face orientations, age, and gender. We automatically estimate the first two parameters from image sequences using CV technology, while the two other parameters are set manually. Finally, we calculate the two-dimensional relationship of multiple persons and visualize it as 3D contours in real-time. Our method can sense and visualize invisible and unconscious PS distributions and convey the spatial relationship of users by an intuitive visual representation. The results of this paper can be used to Human Computer Interaction in public spaces.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5257-5264
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• 2016

Background: Though people of color (POC) are less likely to become afflicted with skin cancer, they are much more likely to die from it due to delay in detection or presentation. Very often, skin cancer is diagnosed at a more advanced stage in POC, making treatment difficult.The purpose of this research was to improve awareness regarding skin cancers in people of color by providing recommendations to clinicians and the general public for early detection and photo protection preventive measures. Methods: Data on different types of skin cancers were presented to POC. Due to limited research, there are few resources providing insights for evaluating darkly pigmented lesions in POC. Diagnostic features for different types of skin cancers were recorded and various possible risk factors were considered. Results: This study provided directions for the prevention and early detection of skin cancer in POC based on a comprehensive review of available data. Conclusions: The increased morbidity and mortality rate associated with skin cancer in POC is due to lack of awareness, diagnosis at a more advanced stage and socioeconomic barriers hindering access to care. Raising public health concerns for skin cancer prevention strategies for all people, regardless of ethnic background and socioeconomic status, is the key to timely diagnosis and treatment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.3
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• pp.45-56
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• 2011

Hyper Text Transfer Protocol(HTTP) is widely used in nearly every network when people access web pages, therefore HTTP traffic is usually allowed by local security policies to pass though firewalls and other gateway security devices without examination. However this characteristic can be used by malicious people. With the help of HTTP tunnel applications, malicious people can transmit data within HTTP in order to circumvent local security policies. Thus it is quite important to distinguish between regular HTTP traffic and tunneled HTTP traffic. Our work of HTTP tunnel detection is based on Support Vector Machines. The experimental results show the high accuracy of HTTP tunnel detection. Moreover, being trained once, our work of HTTP tunnel detection can be applied to other places without training any more.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.89-94
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• 2012

In fact, smoking is prohibited in elevators. It is morally wrong to smoke in elevators. In addition, smoking can be very fatal for our children and for women. In this paper, forensic evidence is submitted to court by people who smoke in elevators. Shots around the face of the person in the elevator extracted partially by scene change detection. Smokers is extracted that the white bar is at the mouth biter. People spouting smoke extraction will proceed in the future. It is extracted by using technology of color histogram, one of the scene change detection method. The extract is a much more accurate extraction ratio than the methods that do not use scene change detection.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.165-170
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• 2022

Lying is nuisance to all, and all liars knows it is nuisance but still keep on lying. Sometime people are in confusion how to escape from or how to detect the liar when they lie. In this research we are aiming to establish a dynamic platform to identify liar by using video analysis especially by calculating the ratio of changes in their appearance when they lie. The platform will be developed using a machine learning algorithm along with the dynamic classifier to classify the liar. For the experimental analysis the dataset to be processed in two dimensions (people lying and people tell truth). Both parameter of facial appearance will be stored for future identification. Similarly, there will be standard parameter to be built for true speaker and liar. We hope this standard parameter will be able to diagnosed a liar without a pre-captured data.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.73-78
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• 2009

In this paper, we developed the care system for older people living alone using the RFID technologies and the living informations. The care system store living informations, extracted through a unconstrained detection method by the RFID tags and readers, into a monitering server. The unconstrained detection method improved a weakness of existing systems that detected a living informations through an infrared sensor, ultrasonic sensor, camera, consumed quantity of the tap water or gas. The result of this study will playa very important role, as a part of a composite older-welfare services. Also, in the future, accumulated living informations will be allowed for a health data of older peoples.

• Journal of Korean Academy of Nursing
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• v.31 no.1
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• pp.139-149
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• 2001

The purpose of this study was to analyze characteristics related to the activity of Daily Living (ADL) and dementia among the elderly people who have Medicaid. The cross-sectional descriptive survey study was a nationwide randomization sampling among the population of elderly families who have Medicaid. The data were collected during the month of October, 1999 and total sample was 1,027 elderly people. There were major findings according to the studies. In the results of the ADL assessment most of elderly people were within the 24 to 45 point range. Also, 63.3% of elderly people who made 45 points do not need help when performing daily activities according to the 15 areas of activity components, and 4.9% of these people couldn't do their daily activities. The results of the Dementia assessment were 70.6% of elderly people were in the normal range, 21.7% have a mild case, and 2.8% have severe case of dementia. These were found by using instruments for mental states, which simplified to items of detection of early dementia. In the result of these tests, there was a significantly positive correlation between ADL and degree of dementia with the pearson correlation coefficients. As a result of these studies, the author recommend to strengthen function and organization of public health like a visiting nurse center for elderly people who are over 65 years old. In addition, the government should apply early detection and management system for dementia in the community continuously and cost-effectively, especially for elderly people who live alone and are vulnerable elderly as our priority.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9077-9083
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• 2014

Background: This study aimed to summarize the potential diagnostic value of serum DKK1 levels in cancer detection. Materials and Methods: Serum DKK1 was measured using enzyme-linked immunosorbent assay in a case-control study. Then we performed a meta-analysis and the pooled sensitivity, specificity, diagnostic odds ratio, and summary receiver operating characteristic (sROC) curves were used to evaluate the overall test performance. Results: Serum DKK1 levels were found to be significantly upregulated in gastric cancer as compared to controls. ROC curve analysis revealed an AUC of 0.636, indicating the test has the potential to diagnose cancer with poor accuracy. The summary estimates of the pooled sensitivity, specificity and diagnostic odds ratio in meta-analysis were 0.55 with a 95% confidence interval (CI) (0.53-0.57), 0.86 (95%CI, 0.84-0.88) and 12.25 (95%CI, 5.31-28.28), respectively. The area under the sROC was 0.85. Subgroup analysis revealed that the diagnostic accuracy of serum DKK1 in lung cancer (sensitivity: 0.69 with 95%CI, 0.66-0.74; specificity: 0.95 with 95%CI, 0.92-0.97; diagnostic odds ratio: 44.93 with 95%CI, 26.19-77.08) was significantly higher than for any other cancer. Conclusions: Serum DKK1 might be useful as a noninvasive method for confirmation of cancer diagnosis, particularly in the case of lung cancer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3384-3400
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• 2021

With the advent of the data era, people pay much more attention to data corruption. Aiming at the problem that the majority of existing schemes do not support corruption detection of ciphertext data stored in cloud environment, this paper proposes a data corruption detection scheme based on ciphertexts in cloud environment (DCDC). The scheme is based on the anomaly detection method of Gaussian model. Combined with related statistics knowledge and cryptography knowledge, the encrypted detection index for data corruption and corruption detection threshold for each type of data are constructed in the scheme according to the data labels; moreover, the detection token for data corruption is generated for the data to be detected according to the data labels, and the corruption detection of ciphertext data in cloud storage is realized through corresponding tokens. Security analysis shows that the algorithms in the scheme are semantically secure. Efficiency analysis and simulation results reveal that the scheme shows low computational cost and good application prospect.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.987-990
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• 2005

An important issue in the field of face recognitions and man-machine interfaces is an automatic detection of faces in visual scenes. it should be computationally fast enough to allow an online detection. In this paper we describe our ongoing work on face detection that models the face appearance by edge orientation and color distribution. We show that edge orientation is a powerful feature to describe objects like faces. We present a method for face region detection using edge orientation and a method for face feature detection using local color information. We demonstrate the capability of our detection method on an image database of 1877 images taken from more than 700 people. The variations in head size, lighting and background are considerable, and all images are taken using low-end cameras. Experimental results show that the proposed scheme achieves 94% detection rate with a resonable amount of computation time.