• Smart Structures and Systems
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• v.5 no.4
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• pp.329-344
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• 2009

Ultrasonic chaotic excitations combined with sensor prediction algorithms have shown the ability to identify incipient damage (loss of preload) in a bolted joint. In this study we examine a physical experiment on a single-bolt aluminum lap joint as well as a three-dimensional physics-based simulation designed to model the behavior of guided ultrasonic waves through a similarly configured joint. A multiple bolt frame structure is also experimentally examined. In the physical experiment each signal is imparted to the structure through a macro-fiber composite (MFC) patch on one side of the lap joint and sensed using an equivalent MFC patch on the opposite side of the joint. The model applies the waveform via direct nodal displacement and 'senses' the resulting displacement using an average of the nodal strain over an area equivalent to the MFC patch. A novel statistical classification feature is developed from information theory concepts of cross-prediction and interdependence. This damage detection algorithm is used to evaluate multiple damage levels and locations.

• Smart Structures and Systems
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• v.3 no.4
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• pp.439-454
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• 2007

In this paper a damage imaging technique using pre-stack migration is developed using Lamb (guided) wave propagation in composite structures for imaging multi damages by both numerical simulations and experimental studies. In particular, the paper focuses on the experimental study using a finite number of sensors for future practical applications. A composite laminate with a surface-mounted linear piezoelectric ceramic (PZT) disk array is illustrated as an example. Two types of damages, one straight-crack damage and two simulated circular-shaped delamination damage, have been studied. First, Mindlin plate theory is used to model Lamb waves propagating in laminates. The group velocities of flexural waves in the composite laminate are also derived from dispersion relations and validated by experiments. Then the pre-stack migration technique is performed by using a two-dimensional explicit finite difference algorithm to back-propagate the scattered energy to the damages and damages are imaged together with the excitation-time imaging conditions. Stacking these images together deduces the resulting image of damages. Both simulations and experimental results show that the pre-stack migration method is a promising method for damage identification in composite structures.

• The Plant Pathology Journal
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• v.34 no.6
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• pp.459-469
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• 2018

Plants and microorganisms (microbes) use information from chemicals such as volatile compounds to understand their environments. Proficiency in sensing and responding to these infochemicals increases an organism's ecological competence and ability to survive in competitive environments, particularly with regard to plant-pathogen interactions. Plants and microbes acquired the ability to sense and respond to biogenic volatiles during their evolutionary history. However, these signals can only be interpreted by humans through the use of state-of the-art technologies. Newly-developed tools allow microbe-induced plant volatiles to be detected in a rapid, precise, and non-invasive manner to diagnose plant diseases. Beside disease diagnosis, volatile compounds may also be valuable in improving crop productivity in sustainable agriculture. Bacterial volatile compounds (BVCs) have potential for use as a novel plant growth stimulant or as improver of fertilizer efficiency. BVCs can also elicit plant innate immunity against insect pests and microbial pathogens. Research is needed to expand our knowledge of BVCs and to produce BVC-based formulations that can be used practically in the field. Formulation possibilities include encapsulation and sol-gel matrices, which can be used in attract and kill formulations, chemigation, and seed priming. Exploitation of biogenic volatiles will facilitate the development of smart integrated plant management systems for disease control and productivity improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1123-1140
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• 2019

Many Internet of Things (IoT) applications involving bursty traffic have emerged recently with event detection. A power management scheme qualified for uplink bursty traffic (PM-UBT) is proposed by distinguishing between bursty and general uplink traffic patterns in the IEEE 802.11 standard to balance energy consumption and uplink latency, especially for stations with limited power and constrained buffer size. The proposed PM-UBT allows a station to transmit an uplink bursty frame immediately regardless of the state. Only when the sleep timer expires can the station send uplink general traffic and receive all downlink frames from the access point. The optimization problem (OP) for PM-UBT is power consumption minimization under a constrained buffer size at the station. This OP can be solved effectively by the bisection method, which demonstrates a performance similar to that of exhaustive search but with less computational complexity. Simulation results show that when the frame arrival rate in a station is between 5 and 100 frame/second, PM-UBT can save approximately 5 mW to 30 mW of power compared with an existing power management scheme. Therefore, the proposed power management strategy can be used efficiently for delay-intolerant uplink traffic in event-driven IoT applications, such as health status monitoring and environmental surveillance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.197-202
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• 2014

It is used the important method that Oriental doctor determines patient's disease status observing patient's state of tongue in Oriental medicine clinic. In this paper, it developed the how to use the pulse diagnosis and tongue diagnosis based on s mart based electronic acupuncture. It will do objective judgment without wrong diagnosis. In this paper, we developed the algorithm that it automatically determines patient health condition and smart electronic acupuncture kit using fuzzy logic and fuzzy reasoning system were completed. In this paper, Simulation results proved that acupuncture is effective than the traditional method of using electronic intelligence.

• Journal of Biomedical Engineering Research
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• v.43 no.4
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• pp.185-192
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• 2022

Early detection of mild cognitive impairment can help prevent the progression of dementia. The purpose of this study was to design and validate a machine learning model that automatically differential diagnosed patients with mild cognitive impairment and identified cognitive decline characteristics compared to a control group with normal cognition using resting-state quantitative electroencephalogram (qEEG) with eyes closed. In the first step, a rectified signal was obtained through a preprocessing process that receives a quantitative EEG signal as an input and removes noise through a filter and independent component analysis (ICA). Frequency analysis and non-linear features were extracted from the rectified signal, and the 3067 extracted features were used as input of a linear support vector machine (SVM), a representative algorithm among machine learning algorithms, and classified into mild cognitive impairment patients and normal cognitive adults. As a result of classification analysis of 58 normal cognitive group and 80 patients in mild cognitive impairment, the accuracy of SVM was 86.2%. In patients with mild cognitive impairment, alpha band power was decreased in the frontal lobe, and high beta band power was increased in the frontal lobe compared to the normal cognitive group. Also, the gamma band power of the occipital-parietal lobe was decreased in mild cognitive impairment. These results represented that quantitative EEG can be used as a meaningful biomarker to discriminate cognitive decline.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.3
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• pp.347-358
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• 2016

The paper presents a software architecture for a wearable device to measure vital signs with the real-time user's behavior recognition. Taking vital signs with a wearable device help user measuring health state related to their behavior because a wearable device is worn in daily life. Especially, when the user is running or sleeping, oxygen saturation and heart rate are used to diagnose a respiratory problems. However, in measuring vital signs, continuosly measuring like the conventional method is not reasonable because motion artifact could decrease the accuracy of vital signs. And in order to fix the distortion, a complex algorithm is not appropriate because of the limited resources of the wearable device. In this paper, we proposed the software architecture for wearable device using a simple filter and the acceleration sensor to recognize the user's behavior and measure accurate vital signs with the behavior state.

• Perspectives in Nursing Science
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• v.7 no.1
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• pp.50-54
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• 2010

The studies of M. Colombo (1989) and W. Lange (1992) showed that 30~40% of people became chronic after suffering from hepatitis B virus (HBV) and C virus (HCV) infection, and about 50% of the chronic cases transformed into primary liver cancer. There have been few studies done in Mongolia on hepatitis infection among health professionals, particularly in nurses. In a study done by Chimedsuren (8), the study showed that 19.4% of people with identified surface hepatitis B antigen (HBsAg) and antibodies to hepatitis C virus and 8% of people with the identified nucleotide of RNA for the hepatitis C virus (polymerase chain reaction) had an acute form of hepatitis C. Studies on the hepatitis virus genome damaging effect on liver cells showed that genotype 8 (A, B, C, D, E, F, G, TTV) had the most damaging effect on liver cells (Hahn and Faeka, 2007). Several studies have shown a relationship between hepatitis B virus infection and a lack of compliance regarding safety regulations and rules by medical personnel. Results of a study from the Maternal and Child Health Research Center showed that tests done to detect hepatitis B virus antigen and antibodies to C virus did not reveal anything. Both antigen and antibodies in 69% cases did not show, and separately, B virus and antibodies to hepatitis C virus were identified in 13% and 9%, respectively. Results of the tests taken from health personnel in Shastin Central Hospital showed that in 76% of the cases, the B virus antigen with C virus antibodies was not identified. In 8% of the cases, the B virus antigen was present on its own. The combination of B the virus antigen and C virus antibodies were present in 8% of nurses and doctors, respectively. 82% of the cases had negative results for the detection of a combination of B virus antigen and C virus antibodies taken from health personnel from the State Central Clinical Hospital whereas the B virus antigen and C virus antibodies by themselves were present in 7% and 14% of the cases, respectively. Combined cases of the B virus antigen and C virus antibodies were identified in 4% of the personnel. Results of the tests taken from the health personnel in the Hospital of the Ministry of Justice and Internal Affairs showed that in 79% of the cases, the B virus antigen with C virus antibodies were not identified. Separately, the B virus and antibodies to hepatitis C virus were identified in 8% and 13% of the cases, respectively.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.625-630
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• 2016

Background: Despite the established role of the Pap smear test (PST) in prevention and early detection of cervical cancer, it is still rarely practiced in Sudan. Many challenges hinder the establishment of an effective cervical cancer screening program, including socio-cultural factors. Therefore, this study aimed to investigate the knowledge, attitudes and practices (KAP) of Sudanese women with regard to the Pap smear test and cervical cancer. Materials and Methods: A total of 500 married women aged 14 to 58 years were recruited from obstetric clinics, hospitals and universities in Khartoum in 2014. Data were collected using a standardized, pretested questionnaire that inquired socio-demographic characteristics and their KAP about cervical cancer and the PST. Results: More than 52% of participating women were above 30 years of age, and the majority (78.8%) were university degree holders. A total of 486 (97.2 %) of participants were resident in urban areas of Khartoum State. However about 48% of the respondents had never heard about PST, and only 15.8% of the participants had undergone a Pap smear test previously; 46.6% (233/500) knew that the human papilloma virus (HPV) was the causative agent, but only 39.2% (196/500) had heard about HPV vaccination, and only 11.4% (57/500) had received the vaccine. However 68% of the respondents agreed to do Pap smear if properly informed about the test and 75.4% of the respondents agreed to participate in a cervical cancer screening program. Conclusions: Despite a high educational level, less than half of our participants had accurate knowledge about cervical cancer, HPV, and cervical cancer screening. Health education about cervical cancer, HPV and sexually transmitted infections and the role of PST in cervical cancer prevention are crucial when designing interventions aimed at improving cervical cancer screening for Sudanese women.

• Journal of Environmental Health Sciences
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• v.40 no.5
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• pp.397-406
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• 2014

Objectives: Perchloroethylene (PCE) is a volatile chemical widely used as a solvent in the dry-cleaning and textile processing industries. It was evaluated as Group 2 "probably carcinogenic to humans" by the Integrated Risk Information System (IRIS) of the United State Environmental Protection Agency (U.S. EPA) in 2012. In order to provide a scientific basis for establishing risk management measures for chemicals on the national priority substances list, aggregate risk assessment was conducted for PCE, included in the top-10 substances. Methods: We conducted the investigation and monitoring of PCE exposure (e.g., exposure scenario, detection levels, and exposure factors, etc.) and assessed its multi-media (e.g., outdoor air, indoor air, and ground water) exposure risk with a deterministic and probabilistic approach. Results: In human risk assessment (HRA), the level of human exposure was higher in the younger age group. The exposure level through inhalation at home was the highest among the exposure routes. Outdoor air or uptake of drinking water represented less than 1% of total contributions to PCE exposure. These findings suggested that the level of risk was negligible since the Hazard Index (HI) induced by HRA was below one among all age groups, with a maximum HI value of 0.17 when reasonable maximum exposure was applied. Conclusion: In conclusion, it was suggested that despite low exposure risk, further studies are needed considering main sources, including occupational exposure.