• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1540-1549
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• 2004

In this paper, we propose an algorithm to detect semantic events in golf video using Hidden Markov Model. The purpose of this paper is to identify and classify the golf events to facilitate highlight-based video indexing and summarization. In this paper we first define 4 semantic events, and then design HMM model with states made up of each event. We also use 10 multiple visual features based on MPEG-7 visual descriptors to acquire parameters of HMM for each event. Experimental results showed that the proposed algorithm provided reasonable detection performance for identifying a variety of golf events.

• Journal of Power Electronics
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• v.16 no.1
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• pp.182-189
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• 2016

Fault detection is the research focus and priority in this study to ensure the high reliability of a proposed three-level inverter. Kernel principal component analysis (KPCA) has been widely used for feature extraction because of its simplicity. However, highlighting useful information that may be hidden under retained KPCs remains a problem. A weighted KPCA is proposed to overcome this shortcoming. Variable contribution plots are constructed to evaluate the importance of each KPC on the basis of sensitivity analysis theory. Then, different weighting values of KPCs are set to highlight the useful information. The weighted statistics are evaluated comprehensively by using the improved feature eigenvectors. The effectiveness of the proposed method is validated. The diagnosis results of the inverter indicate that the proposed method is superior to conventional KPCA.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.3-11
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• 2006

The need for edge detection about topography data from the high resolution satellite imagery is happening with increasing frequency according to many people utilize the its imagery as various fields recently. Many experts is recognizing of other GIS will make use of the road detection from the high resolution satellite imagery, including ITS (Intelligent Transportation Systems) and urban planning. This paper is comparative analysis of LPF (Low Pass Filtering) and HPF (High Pass Filtering) for roads edge detection from high resolution satellite imagery. As a result, LPF and HPF can be highlight selective pixels at edge area about input data. In case or applying to other techniques such as LPF for the same purpose, they aye more effective for wide road width which often cause the slight distortion of boundary or overall change of brightness values on the whole Image. Whereas, HPF has ability to enhance selectively detailed components in a target image.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.559-572
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• 2017

Cyberbullying has been an emerging issue in recent years where research has revealed that users generally spend an increasing amount of time in social networks and forums to keep connected with each other. However, issue arises when cyberbullies are able to reach their victims through these social media platforms. There are different types of cyberbullying and like traditional bullying; it causes victims to feel overly selfconscious, increases their tendency to self-harm and generally affects their mental state negatively. Such situations occur due to security issues such as user anonymity and the lack of content restrictions in some social networks or web forums. In this paper, we highlight the existing solutions, which are Intrusion Prevention System and Intrusion Detection System from a number of researchers. However, even with such solutions, cyberbullying acts still occurs at an alarming rate. As such, we proposed an alternative solution that aims to prevent cyberbullying activities at a younger age, e.g., young children. The application would provide an alternative method to preventing cyberbullying activities among the younger generations in the future.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.2247-2254
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• 2016

Background: The incidence of breast cancer is rising in Oman, and the disease is diagnosed at late stages, when treatment success is limited. Omani women might benefit from better awareness, so that breast cancer can be detected early and treated. This study was conducted to assess Omani women's levels of breast cancer awareness and early detection practice, and explore factors which might influence these levels. Materials and Methods: A mixed methods study was conducted in 2014, including a quantitative survey of 1,372 and a qualitative assessment of 19 Omani women, aged ${\geq}20years$ from five Omani governorates using convenient sampling. Demographic information and scores for awareness levels were used in a multivariate regression model to investigate factors associated with awareness. Thematic analysis and interpretive description were used to analyse the qualitative data. Results: The overall means for early detection and general awareness scores were 0.58 (SD 0.24) and 0.46 (SD 0.21), respectively. General awareness was significantly associated with age, education, income and familiarity with cancer patients (p<0.05), while early detection was significantly associated with age, marital status and education. A majority of women (59.5%) agreed with a belief in 'evil eye' or envy as a risk factor for breast cancer. Women discussed various factors which may empower or inhibit awareness, including the cultural-religion-fatalistic system, personal-familial-environmental system, and healthcare-political-social system. Conclusions: The overall low scores for awareness and early detection, and the survey of local beliefs highlight a severe necessity for a contextually-tailored breast cancer awareness intervention programme in Oman.

• Bulletin of the Korean Chemical Society
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• v.35 no.9
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• pp.2723-2725
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• 2014

Recently we have reported a novel class of anion receptors which are based on 2n-crown-n topology. Trioxane derivatives are capable of anion sensing through pure aliphatic C-H hydrogen bonding. In this work, we highlight another interesting property, i.e., they can also recognize cations as normal crown ethers (3n-crown-n topology). Since the same functional moiety can recognize anions and cations, these coronands are predicted to be amphi-ionophores. However, we could not detect cations even in the gas phase. Considering trioxane is analogous to [$1_6$]starand, this was rather counter-intuitive. The calculation results show that these coronands can detect alkali metals with very low affinity. The low affinity toward cations should be responsible for this failure of experimental detection. With careful theoretical study, we found that this low affinity toward cations could be explained by the unfavorable charge-dipolar moiety orientations as proposed by Cui et al. As in the case of [$1_6$]starand, this is an example that underscores the importance of charge-dipolar moiety orientation in supramolecular interactions.

• Journal of Biomedical Engineering Research
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• v.26 no.5
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• pp.271-282
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• 2005

There are strong demands for accurate, fast, and inexpensive devices in the medical diagnostic laboratories, such as biosensors and chemical sensors. Biosensors can provide the reliable and accurate informations on the desired biochemical parameters, which is an essential prerequisite for a patient before going for a treatment. They can be used for continuous measurements of metabolites, blood cations, gases, etc. Of these, electrochemical biosensors play an important role in the improvement of public health, because rapid detection, high sensitivity, small size, and specificity are achievable for clinical diagnostics. In this paper, the clinical applications with electrochemical biosensors are reviewed. An attempt is also made to highlight some of the trends that govern the research and developments of the important biosensors that are associated to clinical diagnosis.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1067-1074
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• 2014

In Morocco, breast cancer is the most prevalent cancer in women and a major public health problem. Several Moroccan studies have focused on studying this disease, but more are needed, especially at the genetic and molecular levels. It is therefore interesting to establish the genetic and molecular profile of Moroccan patients with breast cancer. In this paper, we will highlight some pertinent hypotheses that may enhance breast cancer care in Moroccan patients. This review will give a precise description of breast cancer in Morocco and propose some new markers for detection and prediction of breast cancer prognosis.

• Journal of Periodontal and Implant Science
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• v.43 no.3
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• pp.111-120
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• 2013

Periodontitis is a common oral disease that is characterized by infection and inflammation of the tooth supporting tissues. While its incidence is highly associated with outgrowth of the pathogenic microbiome, some patients show signs of predisposition and quickly fall into recurrence after treatment. Recent research using genetic associations of candidates as well as genome-wide analysis highlights that variations in genes related to the inflammatory response are associated with an increased risk of periodontitis. Intriguingly, some of the genes are regulated by epigenetic modifications, supposedly established and reprogrammed in response to environmental stimuli. In addition, the treatment with epigenetic drugs improves treatment of periodontitis in a mouse model. In this review, we highlight some of the recent progress identifying genetic factors associated with periodontitis and point to promising approaches in epigenetic research that may contribute to the understanding of molecular mechanisms involving different responses in individuals and the early detection of predispositions that may guide in future oral treatment and disease prevention.