Earticle

This paper develops a new diagnosis model using urine biomarker proteins for early ovarian cancer diagnosis. The optimum marker combination that best classifies the benign tumor and cancer was determined from 15 biomarkers and the performance was evaluated. Samples consist of 121 patients with benign tumor, and 55 patients with ovarian cancer. 15 urine biomarkers showing specific reaction to ovarian cancer was the concentration value obtained from xMAP™ bead-based technology (Luminex Corp.). The area under the curve (AUC) of ROC was evaluated to determine the optimum marker combination showing the best performance in difference between patients diagnosed with ovarian cancer and benign. The performance of the selected combination was confirmed with logistic regression. For each combination of two, three, and four biomarkers showed the highest AUC of 85.71%, 86.38%, and 86.7%, respectively. The highest accuracy of distinguishing benign to cancer was 82.58% for a single biomarker, and 84.27%, 84.83%, and 85.29% for each combination of two, three, and four biomarkers, respectively. It was confirmed that the ovarian cancer diagnosis model utilizing the optimum biomarker combination determined in this research showed better performance and higher accuracy than using a single biomarker.

Graph mining is a dynamic and active research area. In recent years, there is a remarkable boost in graph-structured data resulting graph mining a serious topic in research community. Graph clustering is the process of identifying similar structures in a large set of graphs. Graph clustering is also known as graph partitioning or grouping. This problem plays an important role in various data mining applications. Traditional approaches are centric towards optimization of graph clustering objectives such as ratio association or normalized cut. Spectral methods are also introduced which required Eigen-Vector computation. However these techniques are slow. We have presented a novel algorithm for detecting closely related groups of graph structures in KEGG metabolic pathways. The technique is based on structural similarity of connected fragments in graph-structured data. The technique is scalable to directed as well as undirected graphs. Preliminary experiments with synthesized data collected from KEGG were performed and their results are reported. The second contribution of this study is the modeling and analysis of combined metabolic reaction networks and relation network and showing their behavior towards scale free network.

Aortic blood pressure is more meaningful than brachial blood pressures for clinical diagnosis, and ambulatory blood pressure monitoring is better predictor for the outcomes than clinical blood pressure monitoring. However, there are few devices which provide continuous central blood pressures and arterial stiffness noninvasively. In this study, pressure sensors were developed to detect two radial and one carotid pulse waveforms. Central aortic pulse, two radial pulses and carotid pulse were recorded simultaneously during surgery. Parameters were extracted and the relationships among them were examined. Standard deviations for radial and carotid pulse pressures were all within the range of ±5 mmHg for every experimental setup. Augmentation index from aortic pulse showed much lower value than that from the radial sites, and the values of averaged augmentation index showed different trends, which might be caused by the different force applied to the pressure sensor on the carotid artery. The observed correlation, not only between the RADI SBP and estimated SBP, but also between the pulse pressure measured by the RADI pressure wire and estimated pulse pressure, proved the usefulness of the estimated central blood pressure obtained from the radial pressure pulse waveform using the ARX model.

After the release of the film, ‘Avatar’recently, a new paradigm is emerging in the 3D contents industry worldwide due to the expansion of the 3D contents production. Along with the rapid growth of the 3D contents industry, individual nations are stepping up the effort to develop 3D technology and to secure upper hand in the standardization effort in order to secure the leading position in the marketing sphere. As a result, transformation from 2D to 3D is taking place in the diverse industry areas such as TV, S/W, 3D game contents and others as the 3D technology is being used in diverse areas. However, 3D syndromes such as fatigue of the eyes result when 3D image is watched for a long time since the method of using merely the disparity of two eyes is used when watching 3D image to this day. In addition to this problem, there is a systemic level problem, which is the need to maintain specific distance and location in order to feel the 3D effect correctly. Accordingly, this research paper seeks to leverage the change in the 3D image’s Depth level to present 3D Depth level analysis index that will enable users to feel the three-dimensional effect and engagement level most effectively depending on distance and location, and to capitalize the findings to present 3D image control system that can adjust 3D Depth following the three-dimensional effect felt by user.

The optimization of the mineral nutrition is the key to optimize the production of groundnut, as it has very high nutrient requirement and the recently released high yielding varieties take away still more nutrients from the soil. On contrary severe mineral nutrient deficiencies due to inadequate and imbalance use of nutrients is one of the major factors responsible for low yield in groundnut. Thus, to observe the effect of Phosphorus (P), Calcium (Ca) and Boron (B) on the growth and yield of groundnut cv. BARI Cheenabadam 7, fertilizer doses of P (P0=0, P1= 25 and P2=50 kg ha-1), Ca (Ca0=0, Ca1=110 and Ca2= 165 kg Ca ha-1) and B (0, 2 and 2.5 kg ha-1) were used. Among the growth parameters plant height, number of branches plant-1, dry weight plant-1, LAI and CGR were highest at 100 DAS in P2× Ca1× B2 treatment combination. Among the yield attributing characters number of total pods plant-1 was highest for P1× Ca2× B2, 100 pod weight plant -1 for P1× Ca2× B1, shelling percentage, pod yield, biological yield, straw yield and harvest index for P2× Ca1× B2. The lowest values of all these parameters were found at control treatment. The combined dose of P2, Ca1 and B2 produced the highest values for almost all the above parameters. Thus, it can be concluded that the fertilizer level for P, Ca and B should be 50 kg ha-1, 110 kg ha-1 and 2.5 kg ha-1, respectively for obtaining the highest yield of groundnut under this particular soil.

As our society farther expands, there has been many supports for second-class citizens, disabled. One of many supports that is urgent is the guarantee of mobility for blind people. There has been many efforts but even now, it is not easy for blind people to independently move. In this paper, it constructs and materializes the navigation system for blind people in order to provide precise location information, using Android base Smart Phone. The navigation system uses TTS(Text-to-Speech) for blindness in order to provide a navigation service through voice. Also, it uses Google Map API to apply map information. Suggested system, as an independent program, is fairly cheap and it is possible to install onto Smart phone held by blind people. This allows blind people to easy excess the program. This application tested its performance through Galaxy Player YP-GB1 based on Android 2.2. As the result, the voice support about map information has progressed favorably.

A robust algorithm for finger-gesture-based mobile user interfaces (UIs) is presented. The proposed algorithm adopts edge detection for fingertip detection, which is robust to changes in lighting conditions for mobile UIs based on finger gestures. The proposed algorithm has low complexity, and can easily cope with real-time processing using rear-facing cameras in mobile phones. Experimental results demonstrate that the proposed algorithm has better correct-detection probability than the conventional algorithm in various environments.

This paper proposes Multidirectional Block Ranking based segmentation and removal of Interphase cells from chromosome images. The efficiency of automatic karyotyping decreases with the presence of undivided, condensed mass of chromosomes called Interphase cells, stain, debris and other unwanted interferences in the chromosome image. The algorithm segments and removes these interferences and enhances the accuracy of automatic karyotyping. The method is tested and excellent segmentation accuracy is accomplished. The chromosome image is preprocessed and a boundary-mapping algorithm is applied to identify the Region of Interest (RoI). The image is divided into blocks and ranks are assigned to all the blocks using Gaussian Ranking Functions (GRF) based on their contribution to the RoI. A higher rank is assigned to the block contributing more while a lesser rank is assigned to other blocks that contribute less to the RoI. The Interphase cells that constitute the RoI are removed from the chromosome images based on the cumulative rank obtained by the blocks in the chromosome image. The proposed algorithm is applied to segment and remove Interphase cells, stains, dirt and other particles that exhibit structural homogeneity. The algorithm gives accurate results in applications where the RoI to be segmented share the grey level with the background wherein the traditional image segmentation methods fall short of accomplishing precise segmentation results.

In this paper, we propose a method to predict human emotion based on a multi-dimensional emotion model using sentimental similarity. The proposed framework predicts the user's level of emotional response to an emotional stimulus, based on a sensitivity database that consists of self-assessment manikin-based integer-scale data, rated on various object stimulations by many users. We experimented on 72 users, with 1,073 stimulation objects, based on the International Affective Picture System, and used Thayer's arousal-valence 2-dimensional emotion model to verify the proposed framework. As a result, we have confirmed that the proposed framework can predict user emotion using an arousal-valence model.

Portable devices for providing energy expenditure information have been developed in the area of u-healthcare environment. The body consumes energy not only by body activities but also by voices such as talking and singing, however, current devices calculate energy expenditure values based on body activities only. This study was performed to estimate energy consumption caused by voices using PVDF vibration sensor. Sensing module for acquiring voice transmitted through bone, placed on the sternum area, was fabricated in house. Twenty six subjects were participated for the experiment for data collection while reading book and singing with the use of respiratory gas analyzer. Also, body movement was acquired using 3-axis accelerometer while walking and running on the treadmill with the use of gas analyzer, too. Parameters extracted from the voice signal and accelerometer outputs were compared with the actual energy consumption obtained from gas analyzer for finding linear regression equation. R-square values of voice signal and body activity signal were found to be 0.669 and 0.691, respectively, and the regression equations were established accordingly.

The medical information is very important, nowadays internet-based system deployment is used in medical field due to advantages it has to offer. All the information like patient test results, diagnosis and others are stored in the database. In this paper we discuss an internet-based medical record system and proposed a security mechanism on how to secure the retrieving of the data in the database. Here we use a cryptographic scheme to authenticate the users and give them the right to access base on their function and give the information as response to their query but limited to the scope of their privileges. In this paper we give the very simple authentication method yet, effective and easy to implement. There are two authentication methods, first is the authentication to access the system and second is the authentication to access the data.

This article is devoted to description of threats and actual possible attacks on networks (high-speed and wireless), where agent systems and biometric systems are in use.

Sensitive and selective sensor systems are required to detect causes of disease. We outline the conceptual foundations of the novel approach to sensing based on multi-modal processing of signals of nano-bio sensors. Multi-modal sensing scheme can relax constraints of detecting conditions. It is able to detect the cause of the disease more effectively than single mode of sensor. Some peak detection algorithms which are suitable for portable system are compared to apply to multi-modal nano-bio sensors in this paper. It is shown that auto-threshold peak detection is useful for portable nano-bio sensor system with low cost processor.

Because of the weak authentication system to get permission to access e-learning contents or more sensitive contents such as tests, an advanced remote authentication system is necessary due to the limitation of one-time authentication based on password or personal identification (PIN).To provide the continuous personal identification, we present the possibility of cognitive biometric applications by combining both eye tracking and event relevant potential (ERP) signal of brain waves. To show the possibility of ERP 300 application, the experimental results of gender differences to information technology terminologies presented as target stimulus, and the analyzed results show that P300 can be useful as acontinuous authentication method in e-learning systems.

The significance of role of biomass of tree species in carbon sequestration had long been recognized, but very little attempts have been made to estimate the biomass accumulation and their contribution for sequestration of carbon, especially in mined out areas. Selection of ideal species for carbon sequestration is very important step for restoration of reduced ecosystem. Tectona grandis and Gmelina arborea belonging to family Verbenaceae, are most widely distributed and economically important timber species in India. In the present paper, attempts were made to work out biomass accumulation and carbon sequestration of these species raised in age series of plantations on coal mine overburden of Singrauli, M.P, India, adopting non harvest technique using following steps: volume over bark (vob), standing biomass, carbon of standing tree, biomass accumulation and carbon sequestration and finally, preparation of biomass and carbon tables. On the basis of maximum correlation coefficient and minimum standard error, the best fit equations were computed to be VOB = -0.017 + 0.003D + 0.0014H + 1.899 x 10-5 D2H (R2 =0.986, SE = 0.0049702113); and VOB = -0.009 + 0.003D + 0.000D2 + 4.889x10-5 D2H (R2= 0.979, SE = 0.0070497) for Gmelina arborea and Tectona grandis, respectively and Where, VOB = volume over bark in CMT; D= diameter at breast height in cm; H= total tree height in meter. The growth data was collected for 49 trees of Gmelina arborea and 72 trees of Tectona grandis (above 5 cm diameter at breast height) covering the over burden plantations of Northern Coal Field Limited, Singrauli (M.P.), India. The best fit equation was then applied to determine the accumulation of total biomass (above- and below- ground) and carbon content adopting IPCC guidelines. The trees were selected in plantations of all available ages representing different diameters and heights. The linear correlation between basal area vs volume, DBH vs volume and basal area vs total biomass was found to be significant in both the species. The values of R2 were closer to +1 which indicated the better line fits of the data.

This study aims to understand and analyse the legal status of telemedicine's standards and category, to bring up problems concerning the analysis findings, and to propose desirable legal measures. By considering the plain meaning of "support" in the Article 34 in Medical Act, responsibility limits of the telemedicine is surveyed. Permitted limits of telemedicine practices, responsibility in case of medical accident at a remote location is studied in this paper. Classification of telemedicine practices including remote doctor and local doctor, proposal for the liability, and necessary for the compensation of responsibility rule in the present Medical Act are also suggested.

Fibrinosis, platelet aggregation and thrombosis were the leading hurdles in the patients alleged from myocardial infarction and stroke. Various nutritional factors were influencing the production of multifunctional recombinant staphylokinase variant (Msak – RGD – Hirulog) from salt inducible E.coli GJ1158, which was constructed in our lab. One-factor-at-a-time method was used to investigate the constituents like carbon and nitrogen sources for the best medium composition. Initial optimization was carried out by using L27 - orthogonal array method. The significance of each factor with respect to MRH production was identified by Taguchi (Dextrose Mono Hydrate (DMH), Na2HPO4, KH2PO4, TMM, NH4Cl, Yeast extract and 1M MgSO4) and the specific fibrinolytic activity was increased 1.34 folds (20,058 to 22,763 U/mL). The outcome of taguchi results indicates the dextrose mono hydrate, yeast extract, Na2HPO4 and KH2PO4 are influencing in the production of MRH. Final optimization was carried out using response surface methodology (Central Composite Rotatable Design) and the activity of MRH was significantly enchanced to 1.17 folds (22,763 to 26,758 U/mL). For the first time, cost effective media constituents for enhanced production (960 mg/L) of multi-functional MRH and its activity (26,758 U/mL) was studied.

To improve the research productivity in bioinformatics study by using effective means of large scale data analysis, there are many obstacles that need to be overcome They are standardization of data collection and analysis, management of computing and storage resources, easiness of parallel programming, and efficiency of data analysis job execution, to name a few. Among these, easiness of parallel programming is a crucial factor that contributes to usability and efficiency of large scale data analysis. This paper describes a biologic data analysis platform based on cloud computing infrastructure. The platform provides an easy-to-use parallel data analysis environment, and ultimately enhances the productivity of bioinformatics research.