• Journal of Korean Medicine for Obesity Research
• /
• v.9 no.1
• /
• pp.37-44
• /
• 2009

The study was to investigate the distribution for the diagnosis of pattern identification questionnaire and agreement rate between diagnosis of pattern identification based on obesity pattern identification questionnaire and the clinical diagnosis of pattern' identification by medical specialist. The distribution for the diagnosis of pattern identification based on obesity pattern identification questionnaire was shown in order of stagnation of liver Gi, retention of undigested food, deficiency of Yang at scale of 5, 3, 2 score and the diagnosis rate of single pattern identification at scale of 5, 3, 2 score was 89.96%, 79.33%, 54.64%, respectively the agreement rate between the diagnosis of pattern identification based on obesity pattern identification questionnaire and the clinical diagnosis of pattern identification by medical specialist was 0.1013. Therefore, the complementary management in CRF questionnaires with consultation from experts and the study for score difference of pattern identification will improve the accuracy and agreement rate, which will will be helpful for pattern identification of obesity by clinical experts.

• Smart Structures and Systems
• /
• v.30 no.3
• /
• pp.273-286
• /
• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Asia pacific journal of information systems
• /
• v.15 no.4
• /
• pp.1-26
• /
• 2005

This study was to identify the concepts and dimensions of interactivity and to examine the effect of interactivity on identification, relationship quality, and loyalty of e-brand in Internet sites using structural equation model(SEM). For these purposes, the authors developed several hypotheses. The results are as follows. First, control is not associated with identification, but is positively associated with relationship quality. Second, two-way communication is not associated with identification and relationship quality. Third, responsiveness is associated with identification and relationship quality. Fourth, identification is associated with relationship quality. Fifth, identification is not associated with loyalty, while relationship quality is associated loyalty. This means that identification and relationship quality play the partial mediating roles in the relationship between interactivity and loyalty. At the end of this paper, managerial implications, limitations, and future research directions were suggested.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.3
• /
• pp.107-118
• /
• 1998

Two-phase neuro-system identification method is presented. The 1$^{st}$-phase identification uses conventional neural network mapping for modeling an input-output system. The 2$^{nd}$ -phase modeling is also performed sequentially using the 1$^{st}$-phase modeling errors. In the 2$^{nd}$ a phase modeling, newly generated input signals, which are obtained by summing the 1st-phase modeling error and artificially generated uniform series, are utilized as system's I-O mapping elements. The 1$^{st}$-phase identification is interpreted as a “Real Model” system identification because it uses system's real data(i.e., observations and control inputs) while the 2$^{nd}$ -phase identification as a “Artificial Model” identification because of using artificial data. Experimental results are given to verify that the two-phase neuro-system identification could reduce the overall modeling errors.rrors.

• Speech Sciences
• /
• v.12 no.4
• /
• pp.31-42
• /
• 2005

Recently, Gaussian Mixture Model (GMM), a special form of CHMM, has been applied to speaker identification and it has proved that performance of GMM is better than CHMM. Therefore, in this paper the speaker models based on GMM and a new GMM using the modified EM algorithm are introduced and evaluated for text-independent speaker identification. Various experiments were performed to evaluate identification performance of two algorithms. As a result of the experiments, the GMM speaker model attained 94.6% identification accuracy using 40 seconds of training data and 32 mixtures and 97.8% accuracy using 80 seconds of training data and 64 mixtures. On the other hand, the new GMM speaker model achieved 95.0% identification accuracy using 40 seconds of training data and 32 mixtures and 98.2% accuracy using 80 seconds of training data and 64 mixtures. It shows that the new GMM speaker identification performance is better than the GMM speaker identification performance.

• Journal of Biomedical Engineering Research
• /
• v.28 no.3
• /
• pp.325-331
• /
• 2007

Personal identification is essential for the automatic measurement of biosignal information in home healthcare systems. Personal identification is usually achieved with passive radio frequency identification (RFID), which does little more than store a unique identification number. However, passive RFID is not ideal for automatic identification. We present a user identification system based on radio signal strength indication (RSSI) using ZigBee for active RFID tags. Personal identification is achieved by finding the largest RSSI value from aggregated beacon messages that are periodically transmitted by active RFID tags carried by users. Obtaining reliable person!'.! identification without restricting the orientation requires a certain distance between the closest active RFID tag from the ZED and the second closest tag. The results show that the closest active RFID tag from the ZED and the second closest tag must be at least 70 cm apart to achieve reliable personal identification.

• Computational Structural Engineering : An International Journal
• /
• v.3 no.1
• /
• pp.1-7
• /
• 2003

For system identification of large structures, it is not practical to identify the entire structure due to the prohibitive computational time and difficulty in numerical convergence. This paper explores the possibility of performing system identification at substructure level, taking advantage of reduction in both the number of unknowns and the number of degrees of freedom involved. Another advantage is that different portions (substructures) of a structural system can be identified independently and even concurrently with parallel computing. Two substructural identification methods are formulated on the basis whether substructural approach is used to obtain first-order or second-order model. For substructural first-order model, identification at the substructure level will be performed by means of the Observer/Kalman filter Identification (OKID) and the Eigensystem Realization Algorithm (ERA) whereas identification at the global level will be performed to obtain second-order model in order to evaluate the system's stiffness and mass parameters. In the case of substructural second-order model, identification will be performed at the substructure level throughout the identification process. The efficiency of the proposed technique is shown by numerical examples for multi-storey shear buildings subjected to random forces, taking into consideration the effects of noisy measurement data. The results indicate that both the proposed methods are effective and efficient for damage identification of large structures.

• Electronics and Telecommunications Trends
• /
• v.34 no.6
• /
• pp.164-174
• /
• 2019

This article presents low altitude small drone identification trends at home and abroad. To reduce the dysfunction caused by the proliferation of drones worldwide, there is a growing interest in remote identification technologies that can identify the basic information of the drone. First, this article introduces policy trends in major countries. US, Europe, and China have recently provided recommendations regarding technologies available for the remote identification and tracking of a drone. Next, standardization activities on identification communications and identification systems are introduced. For this, standards organizations for the small drone identification, such as the International Organization for Standardization, IEEE 802, Radio Technical Commission for Aeronautics, International Civil Aviation Organization, and $3^{rd}$ Generation Partnership Project, are investigated. Finally, drone identification technology trends are introduced. In the US and Europe, various drone identification technologies have been studied to identify a drone owner and drone registration information with a drone identifier. In South Korea, drone identification technology is still in its infancy, whereas drone detection and physical counterattack technologies are somewhat more developed. As such, major drone manufacturers are also currently studying and developing drone identification systems.

• Journal of Oral Medicine and Pain
• /
• v.24 no.1
• /
• pp.81-94
• /
• 1999

This study intends to find usefulness of the computer assisted dental identification in mass disaster. The variety of dental characteristics was investigated through the research of dental records of 508 adults. And a computer assisted simulation program was used to evaluate the selectivity of dental identification. Findings were as follows : 1. Combinations of dental characteristics were found 155 types. The most various dental characteristic was showed on the mandibular first molar. 99.0% of subjects had dental characteristics for dental identification. 2. The posterior teeth, in comparison with anterior teeth, showed higher selectivity in dental identification which was enhanced by information on the material, type and cavity of the restoration. 3. The variety of dental characteristics was mainly found on the combinations of missing tooth with the material, type and cavity of the restoration. 4. The computer assisted dental identification program, with informa- tion about one's tooth state, made individual identification possible when there was only a part of the teeth in a corpse. 5. The computer assisted dental identification had considerably high selectivity based on the variety of dental characteristics. And it was also performed faster and preciser than the existing identification methods. Based on the results of this study, there are various combinations of the feature of the tooth itself with dental characteristics caused by a certain type of treatment on the teeth. And using the computer assisted dental identification program based on this, dental identification can be more efficient economically and more useful than any other forensic identification methods.

• Journal of Ecology and Environment
• /
• v.41 no.12
• /
• pp.345-350
• /
• 2017

Background: Ecological research often requires monitoring of a specific individual over an extended period of time. To enable non-invasive re-identification, consistent external marking is required. Treefrogs possess lateral lines for crypticity. While these patterns decrease predator detection, they also are individual specific patterns. In this study, we tested the use of lateral lines in captive and wild populations of Dryophytes japonicus as natural markers for individual identification. For the purpose of the study, the results of visual and software assisted identifications were compared. Results: In normalized laboratory conditions, a visual individual identification method resulted in a 0.00 rate of false-negative identification (RFNI) and a 0.0068 rate of false-positive identification (RFPI), whereas Wild-ID resulted in RFNI = 0.25 and RFNI = 0.00. In the wild, female and male data sets were tested. For both data sets, visual identification resulted in RFNI and RFPI of 0.00, whereas the RFNI was 1.0 and RFPI was 0.00 with Wild-ID. Wild-ID did not perform as well as visual identification methods and had low scores for matching photographs. The matching scores were significantly correlated with the continuity of the type of camera used in the field. Conclusions: We provide clear methodological guidelines for photographic identification of D. japonicus using their lateral lines. We also recommend the use of Wild-ID as a supplemental tool rather the principal identification method when analyzing large datasets.