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Face recognition systems gain flexibility and cost efficiency while being integrated into a wireless network. In this paper, we describe a study on the implementation of facial recognition application system using wireless devices. The facial recognition system transmits the pictures photographed by wireless terminals or smart phones and recognizes/authenticates the faces. This system can be applied to several areas such as indolence management, access management and attendance management. The previous facial recognition systems are mostly based on the wire system but our system uses mobile terminals or smart phones.

In wireless body sensor network (WBSN) environments, diverse factors can affect channel environments. For example, the condition of the channel can be changed due to sensor mobility resulting from movements of the experimenter. In addition, the placement of the sensors can change the channel. In this paper, we analyzed the impact of different sensor placements and body movements on the channel environment by measuring the received signal strength indication (RSSI) and the packet delivery rate (PDR). Diverse experiments were conducted with real sensor devices in an office environment. The sensors were placed on the subject’s stomach, back, and ankle, and data were obtained while the subject stood, walked, and ran. The experimental results showed that the RSSI decreased in accordance with an increase in the activity of the experimenter. They also revealed that the RSSI deviation varied depending on the placement of the sensors.

This experimental study aimed to develop an efficient algorithm for detecting and sorting mango. Using the acquired image, the features of the mango were extracted and used to identify the class of the mango. The extracted features of the mango are perimeter, area, roundness, and percent defect. The roundness and percent defect were used to identify whether the mango’s quality was export, local or reject. The area was used to determine the size of the mango. An optimal threshold was used in segmentation and boundary tracing was used to determine the perimeter. This study becomes significant and may contribute to the perspective of new knowledge on image clustering model.

This paper compares the performance of the combination of biomarkers to distinguish benign tumor from cancer and normal from cancer, from 21 urine biomarkers. Samples consist of 79 healthy women, 119 patients with benign tumor, and 137 patients with ovarian cancer. The concentrations of the 21 biomarkers were extracted using Luminex-PRA. The area under the curve (AUC) of ROC was evaluated to determine the optimum marker combination showing the best performance. The performance of the selected combination was confirmed with logistic regression. The highest AUC value of distinguishing benign tumor from cancer with a combination of two biomarkers and three biomarkers are 87.97% and 91.38%, respectively. And the highest AUC value of distinguishing normal from cancer with a combination of two biomarkers and three biomarkers are 87.39% and 90.68%, respectively. Interestingly, the benign-cancer classification shows a little higher performance than the normal-cancer classification.

This paper proposes the mobile assessment system for shoulder joint rehabilitation. To monitor the patient’s condition during the rehabilitation process, it is necessary to assess the initial condition and monitor the progress before and after the treatment. For the assessment, the shoulder joint angle in certain positions needs to be measured. The proposed system measures and assesses the patient’s joint angles in four different positions using smart sensors embedded in the smartphones such as the accelerometer and the gyroscope. The performance of the proposed system is evaluated by comparing the assessment results with measurements using the goniometer.

The purpose of this study is to examine the short-term impact analysis of a clinical information system adoption on relieving menstrual distress in women. Data were collected from 130 women who took health examination in Y health promotion center from May 13 to June 14, 2013. The results of this study are as follows. Firstly, in terms of raising low abdominal temperature on relieving menstrual distress, the experimental group was significantly higher compared to control group(t=-2.69, p<.05). Secondly, the present research showed that menstrual distress can be reduced to 54.2-67.8% by intervention. In conclusion, this paper resulted in significant positive effects on relieving menstrual distress and its implications could be used as the basic data for developing further systematic materials on relieving menstrual distress.

It is evident from various researches that disease diagnosis using machine learning methods has been increasing rapidly. In this research work, feature selection based Least Square Twin Support Vector Machine (LSTSVM), which is a machine learning method, is used for diagnosis of heart diseases. In this approach F-score is used to calculate the weight of each feature and then features are selected according to their weight. The higher weight is assigned to the feature having high F-score. Grid search approach is also utilized to select the best value of classifier's parameters in order to enhance its performance. The heart-statlog disease dataset is used in this study, which is taken from the UCI repository. The performance of proposed model with different feature sets has been evaluated for different training-test datasets. The results indicate that LSTSVM model with 11 features has achieved highest accuracy. The results are very promising as compared to the other approaches proposed earlier.

In this paper, we developed a health pre-diagnosis system with ART2 neural network for Pet dog health monitoring. This system is for the pet owner who does not have deep knowledge on the pet diseases nor computer technology. The standardized database of symptoms/diseases associations is constructed from textbooks and the user simply gives the most unusual symptom that is found from the dog and then the communication between the user and the system refines and expands the input symptoms through queries. Then an unsupervised ART2 learning system checks the similarity between input and stored diseases with confidence and generates three most probable diseases as output. The system has incremental learning ability and learning by experience ability thus appropriately changes the database over time even without user’s database update. In spite of the fact that the system is ad-hoc in nature, the system’s performance is verified by veterinarian as adequate and it can stimulate the owner’s attention on the dog’s abnormality in time such that appropriate professional treatment is given in its early stage.

This research was conducted on experimental analysis of spray and combustion characteristics of six different biodiesels in a constant chamber using a common-rail injection system. The processes of atomization and flame developments were visualized by using a high digital camera under two different injection pressures. The pressure changes were measured by a piezometer pressure sensor, and combustion processes were analyzed by computing heat release rates. From these results, it was concluded that highly pressurized injection accelerated atomization of fuels and caused to shorten ignition delay period and thus improved overall combustion characteristics. In particular, the oxygen contents included in biodiesel accelerated combustion conditions. Furthermore, these quantitative and reliable data of biodiesel fuels which might be useful in supporting their applicability and establishing emission reduction measure in future as well.

Microbial biofilms on biomaterial implant surfaces or devices are troublesome, since biofilm organisms are protected by matrix of exopolymeric substances, impenetrable for most antibiotics and immune cells. It is established that bacterial adhesion to surface is required for colonization and subsequent biofilm formation. The adherent state is important for bacterial survival and development of infection. Therefore, prevention of bacterial adhesion and biofilm growth on implant surfaces should ultimately prevent the occurrence of infection. Egg white was considered to play an important role in resistance against bacteria for developing embryo mainly during early incubation. Utilization of egg white as a coating to prevent bacterial adhesion and biofilm growth on biomaterials implants is novel. Here, we studied the effect of Hen egg white as a coating to surface, on bacterial (Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli) adhesion and biofilm growth. We report that a significant reduction in bacterial adhesion was observed for S.aureus on egg white coated surface compared to control (no egg white coating). Whereas P. aeruginosa and E. coli, do not show any significant difference compared to control. When bacteria were allowed to grow in the presence of egg white, a significant reduction in growth was observed on all bacteria compared to control. Thus Hen egg white potentially used as biological coating on implants for prevention of bacterial adhesion and biofilm formation.

Basigin/EMMPRIN/CD147 has been reported to be associated with inflammatory diseases and cancers. Detailed insight into this multifunctional protein in the context of cellular functions may provide a key to its pathophysiological role in many diseases. Here, we investigated the potential role of basigin in activation of the NF-B and AP-1 signaling cascades associated with the MyD88 and TRIF adaptor proteins. MyD88- and TRIF-dependent activation of NF-B signaling pathway was inhibited by basigin-specific antibody and siRNA. In addition, induction of TRIF-dependent, but MyD88-independent, AP-1 activation was inhibited by basigin-specific siRNA. Taken together, these results suggest that basigin plays a key regulatory role in activation of MyD88- and TRIF-mediated cell signaling pathways, and provide an important insight into basigin-mediated cellular processes that can serve as a guide for the development of new anti-inflammatory therapeutics via intervention in basigin-mediated cellular functions.

The significance of role of biomass of tree species in carbon sequestration has long been recognized. In the present paper, attempts have been made to work out biomass accumulation and carbon sequestration by Pongamia pinnata (Linn) Pierre raised on coal mine overburden of Northern Coal Field Limited, Singrauli (India), adopting non harvest technique. The age of plantation varied from 2 to 18 years. The correlation between basal area vs volume, dbh vs volume and basal area vs total biomass was found to be significant. In terms of vertical and horizontal growth, Pongamia pinnata proved as an efficient species. The net biomass production and carbon sequestration of Pongamia pinnata showed increasing trend with the age of plantations.

DICOM (Digital Imaging and Communications in Medicine) which is standard of PACS(Picture Archiving Communication System) is set up as draft international standard for the purpose of collection and exchange the data and image among main medical display equipments. Medical display equipments is normally utilized as connected feature with surgery monitoring devices like endoscope, X-lay camera. However, most of medical surgery monitoring devices are not adaptable for DICOM, thus it is diffcult to connect data thru PACS. We suggest the connection methodology for PACS and medical surgery monitoring devices by implementation of HL7 interface which can share the medical information with DICOM. The standard DICOM interface module suggested in this thesis creates DICOM IOD (Information Object Definition) information class according to the checkup information received by HIS (Hospital Information System) and also creates standard DICOM format after blending with surgery monitoring data.

This study is to develop the double matrix capsulation biotechnology in order to increase the conservativeness and stability of lactobacillus bacteria, to be deliciously flavored and give it visually differential effect in healthy food industries, were described. In order to eat easy for wellbeing life science, as the first capsulation with o/w (oil-in-water) emulsifying system, our study group was especially made to soft and moisture cream using 5wt% of sucrose ester emulsifier as the first capsule containing lactobacillus bacteria. Nutrient agents were used with botanical squalane, camellia japonica seed oil. Double matrix capsulation was formed with the best stabilized bead type capsules when it blended 1 : 3 ratio of chitosan and sodium alginate. The bead diameter size was about 2.0~5.0mm (mean diameter: 3.8mm). Activity of lactobacillus bacteria containing sweet cream for depending on various pH variations showed that alkalinity (pH=10.8±0.8) condition was higher than acidity (pH=4.2±0.3) and neutrality (pH=713±0.2) conditions. After a month, it also was certified to the activity of lactobacillus bacteria in incubated at 37±3℃ in culture medium. As application of food industry, we developed the containing lactobacillus bacteria capsule and 4 colored kinds of double matrix capsulation in commercial yogurt cream. As for above mentioned those of results, one of tool to stabilize the living lactobacillus bacteria, doubled matrix capsulation greatly be expected to contribute to food industry. Furthermore, it can be expected to apply the drug delivery system (DDS) having good healthy food with active ingredients of stabilizing technologies at drugs, pharmaceutical divisions and skin care cosmetic industry.

The need of similarity measures in life science is ever paramount given the modern biotechnology in producing and storing biomedical datasets in large amounts. This paper presents a novel scheme in measuring similarity of two datasets by prediction class, namely SPC. SPC offers an alternative approach to traditionally used ones such as pairwise correlations which assume every attribute carries equal importance. The unique advantage of SPC is the use of a machine learning model called Fuzzy Unordered Rule Induction to infer the similarity between two datasets based on their common attributes and their degrees of relevance pertaining to a predicted class. The method is demonstrated by a case of comparing lung cancer dataset and heart disease dataset.

There are two types of fuel supply method in CNG vehicles. One is premixed ignition and the other is gas-jet ignition. In premixed ignition, the fuel is introduced with intake air so that homogeneous air-fuel mixture may form. The ignitability of this method depends on the global equivalence ratio. In gas-jet ignition, CNG is introduced directly into the engine combustion chamber. The overall mixture is stratified by retarded fuel injection. In this study, a visualization technique was employed to obtain fundamental properties regarding overall mixture formation and combustion characteristics of direct injected CNG fuel inside a constant volume chamber and engine. For gas-jet visualization, Schlieren high speed imaging is used with the effects of ambient pressure and impingement wall on mixture formation being investigated.

Medical image processing is an multifaceted field at the intersection of computer science, electrical engineering, physics, mathematics and medicine. Medical Image processing has developed versatile computational and mathematical methods for solving problems pertain-ing to medical images and their use for biomedical research and clinical care. The prominent and important motive of Medical Image Processing is to extract clinically relevant infor-mation or knowledge from medical images. MIP focuses on the computational analysis of the images, not their acquisition. The methods can be grouped categorized as: image segmenta-tion, image registration, image-based physiological modeling, Research in Medical Image Processing (MIP) is mainly driven by a technology oriented point of view. MIP research should always be able to give an answer to the question of what is the potential benefit of a solved MIP problem or a newly developed MIP-based system supporting a diagnostic or therapeutic process, in terms of outcome criteria like, e.g., Quality Adjusted Life Years (QALYs) for the patient or cost savings in health care. This paper presents the concept and the strategy of how the Most Relevant MIP problems (MRMIP) shall be identified and as-sessed in the context of improving evaluation of MIP solutions.

This study was designed the bio parameter detector combination system of static posture for reformation by the stability. We used a model of bio-sensor combination system on the basis of the static state in the standing posture. To evaluate the condition (Vision, Vestibular, Somatosensory and CNS), we compared the horizontal movement of average derived from the estimated eye open state in the body moving before(α-μBENO) to horizontal movement of average derived from the estimated eye close state in the body moving before(α-μBENC). As the model depends on the bio-sensor combination system of body moving, average values of these variation were computed (0.01Hz~2Hz, range of Fourier frequency). These systems consist of a data acquisition system for capturing and sending data signal, and to gather a data signal processing, and to control a feedback system. There were evaluated their body sway, and identified to maintain the stability.