• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
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• pp.15-18
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• 2007

Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e. both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion is considered at decision level. The proposed algorithm is tested on the NLPR database.

• Safety and Health at Work
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• 제6권2호
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• pp.104-113
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• 2015

Background: Given the long hours on the road involving multiple and interacting work stressors (i.e., delivery pressures, irregular shifts, ergonomic hazards), commercial drivers face a plethora of health and safety risks. Researchers goal was to determine whether and to what extent long-haul trucker work schedules influence sleep duration and quality. Methods: Survey and biometric data collected from male long-haul truck drivers at a major truckstop in central North Carolina over a six month period. Results: Daily hours worked (mean = 11 hours, 55 minutes) and frequency of working over government-mandated daily HOS regulations (23.8% "frequently or always") were statistically significant predictors of sleep duration. Miles driven per week (mean = 2,812.61), irregular daily hours worked (63.8%), and frequency of working over the daily hour limit (23.8% "frequently or always") were statistically significant predictors of sleep quality. Conclusion: Implications of findings suggest a comprehensive review of the regulations and operational conditions for commercial motor vehicle drivers be undertaken.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권2호
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• pp.117-137
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• 2010

Iris recognition is a biometric technique which uses unique iris patterns between the pupil and sclera. The advantage of iris recognition lies in high recognition accuracy; however, for good performance, it requires the diameter of the iris to be greater than 200 pixels in an input image. So, a conventional iris system uses a camera with a costly and bulky zoom lens. To overcome this problem, we propose a new method to restore a low resolution iris image into a high resolution image using a single image. This study has three novelties compared to previous works: (i) To obtain a high resolution iris image, we only use a single iris image. This can solve the problems of conventional restoration methods with multiple images, which need considerable processing time for image capturing and registration. (ii) By using bilinear interpolation and a constrained least squares (CLS) filter based on the degradation model, we obtain a high resolution iris image with high recognition performance at fast speed. (iii) We select the optimized parameters of the CLS filter and degradation model according to the zoom factor of the image in terms of recognition accuracy. Experimental results showed that the accuracy of iris recognition was enhanced using the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.4076-4092
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• 2019

Nowadays, most users access internet through mobile applications. The common way to authenticate users through websites forms is using passwords; while they are efficient procedures, they are subject to guessed or forgotten and many other problems. Additional multi modal authentication procedures are needed to improve the security. Behavioral authentication is a way to authenticate people based on their typing behavior. It is used as a second factor authentication technique beside the passwords that will strength the authentication effectively. Keystroke dynamic rhythm is one of these behavioral authentication methods. Keystroke dynamics relies on a combination of features that are extracted and processed from typing behavior of users on the touched screen and smart mobile users. This Research presents a novel analysis in the keystroke dynamic authentication field using two features categories: timing and no timing combined features. The proposed model achieved lower error rate of false acceptance rate with 0.1%, false rejection rate with 0.8%, and equal error rate with 0.45%. A comparison in the performance measures is also given for multiple datasets collected in purpose to this research.

• Asian-Australasian Journal of Animal Sciences
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• 제32권8_spc호
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• pp.1275-1283
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• 2019

Goats (Capra hircus) were domesticated during the late Neolithic, approximately 10,500 years ago, and humans exerted minor selection pressure until fairly recently. Probably the largest genetic change occurring over the millennia happened via natural selection and random genetic drift, the latter causing genes to be fixed in small and isolated populations. Recent human-influenced genetic changes have occurred through biometrics and genomics. For the most part, biometrics has concentrated upon the refining of estimates of heritabilities and genetic correlations. Heritabilities are instrumental in the calculation of estimated breeding values and genetic correlations are necessary in the construction of selection indices that account for changes in multiple traits under selection at one time. Early genomic studies focused upon microsatellite markers, which are short tandem repeats of nucleic acids and which are detected using polymerase chain reaction primers flanking the microsatellite. Microsatellite markers have been very important in parentage verification, which can impact genetic progress. Additionally, microsatellite markers have been a useful tool in assessing genetic diversity between and among breeds, which is important in the conservation of minor breeds. Single nucleotide polymorphisms are a new genomic tool that have refined classical BLUP methodology (biometric) to provide more accurate genomic estimated breeding values, provided a large reference population is available.

• 문화기술의 융합
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• 제9권6호
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• pp.1065-1071
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• 2023

본 논문에서는 주거지 내의 재실자의 행동을 분류하기 위한 LSTM 모델을 개발하는 연구에 대해 다룬다. 다중센서의 구성은 실내 공기질을 측정하는 IAQ(Indoor air quality) 센서, 재실감지 및 위치를 추적하는 UWB 레이더, 재실자의 생체정보를 측정하기 위한 Piezo 센서로 구성되며 실제 주거환경과 유사한 실험환경을 구축하여 외출, 재실, 요리, 청소, 운동, 수면 등의 재실자 행동 데이터를 수집한다. 수집한 데이터를 이상치와 결측치를 전처리 후 LSTM 모델을 사용하여 재실자 행동 분류 모델의 정확도, 민감도, 특이도, 그리고 T1스코어를 계산 후 평가한다.

• Journal of Information Processing Systems
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• 제16권1호
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• pp.6-29
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• 2020

Biometrics identification using multiple modalities has attracted the attention of many researchers as it produces more robust and trustworthy results than single modality biometrics. In this paper, we present a novel multimodal recognition system that trains a deep learning network to automatically learn features after extracting multiple biometric modalities from a single data source, i.e., facial video clips. Utilizing different modalities, i.e., left ear, left profile face, frontal face, right profile face, and right ear, present in the facial video clips, we train supervised denoising auto-encoders to automatically extract robust and non-redundant features. The automatically learned features are then used to train modality specific sparse classifiers to perform the multimodal recognition. Moreover, the proposed technique has proven robust when some of the above modalities were missing during the testing. The proposed system has three main components that are responsible for detection, which consists of modality specific detectors to automatically detect images of different modalities present in facial video clips; feature selection, which uses supervised denoising sparse auto-encoders network to capture discriminative representations that are robust to the illumination and pose variations; and classification, which consists of a set of modality specific sparse representation classifiers for unimodal recognition, followed by score level fusion of the recognition results of the available modalities. Experiments conducted on the constrained facial video dataset (WVU) and the unconstrained facial video dataset (HONDA/UCSD), resulted in a 99.17% and 97.14% Rank-1 recognition rates, respectively. The multimodal recognition accuracy demonstrates the superiority and robustness of the proposed approach irrespective of the illumination, non-planar movement, and pose variations present in the video clips even in the situation of missing modalities.

• 한국지능시스템학회논문지
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• 제18권1호
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• pp.72-77
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• 2008

개인 식별 연구는 보안, 감시 시스템에서 중요한 부분이다. 최선의 성능을 가진 시스템을 설계하기 위하여 감지기들로부터 최대 정보를 이용할 수 있도록 설계한다. 다양한 생체 인식 시스템은 등록, 확인, 또는 개인 식별을 위하여 생리 특성이나 행동 특성을 하나이상 활용한다. 발걸음 인식만을 가지고는 아직 개인별 변별적 특징을 안정적으로 나타내지 못하므로, 본 논문에서는 얼굴과 발걸음을 결합한 개인 식별 시스템을 제안한다. 본 논문에서 우리는 한 개의 카메라를 이용한다. 즉, 얼굴과 발걸음 인식 모두 하나의 카메라를 이용하여 획득된 같은 이미지 셋을 사용한다. 본 논문의 중점은 이미지들에서 이용할 수 있는 최대 정보량을 활용하는 것으로 시스템의 성능을 향상시키는 것이다. 결합은 결정 단계에서 고려된다. 제안된 알고리듬은 NLPR 데이터베이스를 사용한다.

• International Journal of Industrial Entomology and Biomaterials
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• 제27권2호
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• pp.243-264
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• 2013

Antheraea mylitta Drury is a commercial silk producing forest insect in India and Xanthopimpla pedator Fabricius is its larval-pupal endoparasitoid, which causes pupal mortality that affects seed production. Effects of host plants, rearing season and their interactions on parasitic behaviour of X. pedator were studied here, as influence of these factors on biological success of X. pedator is not known. Seven forest tree species were tested as food plants for A. mylitta, and rate of pupal parasitization in both the rearing seasons were recorded and analysed. Results showed that rearing season and host plants significantly affected the rate of pupal parasitization in both the sexes. Pupal mortality was found significantly higher (14.52%) in second rearing season than the first (2.89%). Likewise, host plants and rearing seasons significantly affected length, diameter, and shell thickness of cocoons in both sexes. Out of all infested pupae, 85.59% were found male, which indicated that X. pedator chooses male spinning larva of A. mylitta for oviposition, but we could not answer satisfactorily the why and how aspect of this sex specific parasitic behaviour of X. pedator. Multiple regression analysis indicated that length and shell thickness of male cocoons are potential predictors for pupal parasitization rate of X. pedator. Based on highest cocoon productivity and lowest pupal mortality, Terminalia alata, T. tomentosa, and T. arjuna were found to be the most suitable host plants for forest based commercial rearing of A. mylitta in tropical forest areas of Uttarakhand state, where it has never been reared earlier. Sex and season specific interaction of X. pedator with its larval-pupal host, A. mylitta is a novel entomological study to find out explanations for some of the unresolved research questions on parasitic behaviour of X. predator that opens a new area for specialised study on male specific parasitization in Ichneumonidae.

• 환경영향평가
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• 제22권6호
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• pp.591-607
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• 2013

본 연구에서는 생물학적 바이오마커, 물리적 서식지 지표 및 화학적 수질지표를 종합하여 12-메트릭 생태평가 모형을 확립하였고, 도심하천에 적용하여 수생태계 평가를 실시하였다. 생태모형 적용을 위해 도심하천의 상류역의 대조군 지역($C_Z$), 중류의 전이대($T_Z$) 및 하류역의 오염지역(IZ)을 선정한 후, 모델값에 대한 계절별 변이특성을 분석하였다. DNA 손상도 분석은 혈액을 이용한 단세포 전기영동법(Single-cell gel electrophoresis, SCGE)인 Comet assay 지표에 의거한 생지표 메트릭으로 이용되었고, Tail moment, Tail DNA(%) 및 Tail length(${\mu}m$)값이 분석되었다. DNA의 손상은 하류역의 오염지역($I_Z$)에서 분명하게 나타났지만, 대조군($C_Z$) 지역에서는 그렇지 않았다. 개체군 지표로서 비만도 지수인 $C_F$ 값 분석, 체장빈도 분포 지표 및 개체 이상도(Abnormality) 지표가 생물지표로서 이용되었다. 물리적 서식지 지표는 QHEI 모델을 이용하였고, 4개 메트릭이 분석되었다. 화학적 수질지표는 부영양화 지표인 인(P)/질소(N), 화학적 산소요구량 및 전기전도도 지표가 이용되었다. 본 연구를 종합해보면, 12-메트릭 생태모형의 생지표 속성은 대조군($C_Z$)지역에 비해 오염지역($I_Z$)에서 화학적 스트레스 지표(부영양화 지표)에 아주 민감하게 반응 하는 것으로 나타났으며, 또한 이들은 부분적으로 서식지 평가지표에 의해 영향 받는 것으로 분석되었다.