Extraction of Fetal Heart Rate and Fetal Heart Rate Variability from Mother's ECG Signal

This paper describes a new method for extracting the fetal heart rate (fHR) and the fetal heart rate variability (fHRV) signal non-invasively using abdominal maternal electrocardiogram (mECG) recordings. The extraction is based on the fundamental frequency (Fourier-s) theorem. The fundamental frequency of the mother-s electrocardiogram signal (fo-m) is calculated directly from the abdominal signal. The heart rate of the fetus is usually higher than that of the mother; as a result, the fundamental frequency of the fetal-s electrocardiogram signal (fo-f) is higher than that of the mother-s (fo-f > fo-m). Notch filters to suppress mother-s higher harmonics were designed; then a bandpass filter to target fo-f and reject fo-m is implemented. Although the bandpass filter will pass some other frequencies (harmonics), we have shown in this study that those harmonics are actually carried on fo-f, and thus have no impact on the evaluation of the beat-to-beat changes (RR intervals). The oscillations of the time-domain extracted signal represent the RR intervals. We have also shown in this study that zero-to-zero evaluation of the periods is more accurate than the peak-to-peak evaluation. This method is evaluated both on simulated signals and on different abdominal recordings obtained at different gestational ages.

Mining Correlated Bicluster from Web Usage Data Using Discrete Firefly Algorithm Based Biclustering Approach

For the past one decade, biclustering has become popular data mining technique not only in the field of biological data analysis but also in other applications like text mining, market data analysis with high-dimensional two-way datasets. Biclustering clusters both rows and columns of a dataset simultaneously, as opposed to traditional clustering which clusters either rows or columns of a dataset. It retrieves subgroups of objects that are similar in one subgroup of variables and different in the remaining variables. Firefly Algorithm (FA) is a recently-proposed metaheuristic inspired by the collective behavior of fireflies. This paper provides a preliminary assessment of discrete version of FA (DFA) while coping with the task of mining coherent and large volume bicluster from web usage dataset. The experiments were conducted on two web usage datasets from public dataset repository whereby the performance of FA was compared with that exhibited by other population-based metaheuristic called binary Particle Swarm Optimization (PSO). The results achieved demonstrate the usefulness of DFA while tackling the biclustering problem.

A Neural Network Approach in Predicting the Blood Glucose Level for Diabetic Patients

Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.

Classification of Non Stationary Signals Using Ben Wavelet and Artificial Neural Networks

The automatic classification of non stationary signals is an important practical goal in several domains. An essential classification task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "Ben wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.

Angular-Coordinate Driven Radial Tree Drawing

We present a visualization technique for radial drawing of trees consisting of two slightly different algorithms. Both of them make use of node-link diagrams for visual encoding. This visualization creates clear drawings without edge crossing. One of the algorithms is suitable for real-time visualization of large trees, as it requires minimal recalculation of the layout if leaves are inserted or removed from the tree; while the other algorithm makes better utilization of the drawing space. The algorithms are very similar and follow almost the same procedure but with different parameters. Both algorithms assign angular coordinates for all nodes which are then converted into 2D Cartesian coordinates for visualization. We present both algorithms and discuss how they compare to each other.

Association Rule and Decision Tree based Methodsfor Fuzzy Rule Base Generation

This paper focuses on the data-driven generation of fuzzy IF...THEN rules. The resulted fuzzy rule base can be applied to build a classifier, a model used for prediction, or it can be applied to form a decision support system. Among the wide range of possible approaches, the decision tree and the association rule based algorithms are overviewed, and two new approaches are presented based on the a priori fuzzy clustering based partitioning of the continuous input variables. An application study is also presented, where the developed methods are tested on the well known Wisconsin Breast Cancer classification problem.

Evaluation on the Viability of Combined Heat and Power with Different Distributed Generation Technologies for Various Bindings in Japan

This paper has examined the energy consumption characteristics in six different buildings including apartments, offices, commercial buildings, hospitals, hotels and educational facilities. Then 5-hectare (50000m2) development site for respective building-s type has been assumed as case study to evaluate the introduction effect of Combined Heat and Power (CHP). All kinds of CHP systems with different distributed generation technologies including Gas Turbine (GT), Gas Engine (GE), Diesel Engine (DE), Solid Oxide Fuel Cell (SOFC) and Polymer Electrolyte Fuel Cell (PEFC), have been simulated by using HEATMAP, CHP system analysis software. And their primary energy utilization efficiency, energy saving ratio and CO2 reduction ratio have evaluated and compared respectively. The results can be summarized as follows: Various buildings have their special heat to power ratio characteristics. Matching the heat to power ratio demanded from an individual building with that supplied from a CHP system is very important. It is necessary to select a reasonable distributed generation technologies according to the load characteristics of various buildings. Distributed generation technologies with high energy generating efficiency and low heat to power ratio, like SOFC and PEFC is more reasonable selection for Building Combined Heat and Power (BCHP). CHP system is an attractive option for hotels, hospitals and apartments in Japan. The users can achieve high energy saving and environmental benefit by introducing a CHP systems. In others buildings, especially like commercial buildings and offices, the introduction of CHP system is unreasonable.

Classification of Soil Aptness to Establish of Panicum virgatum in Mississippi using Sensitivity Analysis and GIS

During the last decade Panicum virgatum, known as Switchgrass, has been broadly studied because of its remarkable attributes as a substitute pasture and as a functional biofuel source. The objective of this investigation was to establish soil suitability for Switchgrass in the State of Mississippi. A linear weighted additive model was developed to forecast soil suitability. Multicriteria analysis and Sensitivity analysis were utilized to adjust and optimize the model. The model was fit using seven years of field data associated with soils characteristics collected from Natural Resources Conservation System - United States Department of Agriculture (NRCS-USDA). The best model was selected by correlating calculated biomass yield with each model's soils-based output for Switchgrass suitability. Coefficient of determination (r2) was the decisive factor used to establish the 'best' soil suitability model. Coefficients associated with the 'best' model were implemented within a Geographic Information System (GIS) to create a map of relative soil suitability for Switchgrass in Mississippi. A Geodatabase associated with soil parameters was built and is available for future Geographic Information System use.

Method of Intelligent Fault Diagnosis of Preload Loss for Single Nut Ball Screws through the Sensed Vibration Signals

This paper proposes method of diagnosing ball screw preload loss through the Hilbert-Huang Transform (HHT) and Multiscale entropy (MSE) process. The proposed method can diagnose ball screw preload loss through vibration signals when the machine tool is in operation. Maximum dynamic preload of 2 %, 4 %, and 6 % ball screws were predesigned, manufactured, and tested experimentally. Signal patterns are discussed and revealed using Empirical Mode Decomposition(EMD)with the Hilbert Spectrum. Different preload features are extracted and discriminated using HHT. The irregularity development of a ball screw with preload loss is determined and abstracted using MSE based on complexity perception. Experiment results show that the proposed method can predict the status of ball screw preload loss. Smart sensing for the health of the ball screw is also possible based on a comparative evaluation of MSE by the signal processing and pattern matching of EMD/HHT. This diagnosis method realizes the purposes of prognostic effectiveness on knowing the preload loss and utilizing convenience.

Supportability Analysis in LCI Environment

Starting from the basic pillars of the supportability analysis this paper queries its characteristics in LCI (Life Cycle Integration) environment. The research methodology contents a review of modern logistics engineering literature with the objective to collect and synthesize the knowledge relating to standards of supportability design in e-logistics environment. The results show that LCI framework has properties which are in fully compatibility with the requirement of simultaneous logistics support and productservice bundle design. The proposed approach is a contribution to the more comprehensive and efficient supportability design process. Also, contributions are reflected through a greater consistency of collected data, automated creation of reports suitable for different analysis, as well as the possibility of their customization according with customer needs. In addition to this, convenience of this approach is its practical use in real time. In a broader sense, LCI allows integration of enterprises on a worldwide basis facilitating electronic business.

Finite Element Analysis for Damped Vibration Properties of Panels Laminated Porous Media

A numerical method is proposed to calculate damping properties for sound-proof structures involving elastic body, viscoelastic body, and porous media. For elastic and viscoelastic body displacement is modeled using conventional finite elements including complex modulus of elasticity. Both effective density and bulk modulus have complex quantities to represent damped sound fields in the porous media. Particle displacement in the porous media is discretised using finite element method. Displacement vectors as common unknown variables are solved under coupled condition between elastic body, viscoelastic body and porous media. Further, explicit expressions of modal loss factor for the mixed structures are derived using asymptotic method. Eigenvalue analysis and frequency responded were calculated for automotive test panel laminated viscoelastic and porous structures using this technique, the results almost agreed with the experimental results.

From F2F to Online Sessions: Changing Pattern of Instructions in Open and Distance Learning in India

This paper presents an assessment study conducted among the distance learners in India. Open and distance learning systems have traveled a long way since its inception and its journey has witnessed the evolution and adoption of different generations of technology. This study focuses on the distant learners in India. Sampling for this study has been derived from the mass enrollment from Tamil Nadu area, a southern state of India. Learners were chosen from dual mode universities, private universities, Tamil Nadu Open University and IGNOU. The main focus of the study is to examine the coverage and appropriation of students support services and learning aids. It explores two aspects: the facilities available and the awareness and use of such services. It includes, self-learning materials, face-to-face counseling, multimedia learning materials, website, e-learning, radio and television services etc. While exploring the student-s perspective on these learning aspects, it is important to understand the perspectives of the teachers. Two different interests are visible among the teachers. Majority of the teachers support faceto- face counseling. However, the young teachers are in favour of online learning and multimedia supports in teaching. Through the awareness is somewhat high, the actual participation in online is very low. This is due to the inadequate infrastructure as well as the traditional attitudes of the teachers. Still the face-to-face sessions remain popular than online.

Modeling Approach to the Specific Tactical Activities

The contribution deals with current or potential approaches to the modeling and optimization of tactical activities. This issue takes on importance in recent times, particularly with the increasing trend of digitized battlefield, the development of C4ISR systems and intention to streamline the command and control process at the lowest levels of command. From fundamental and philosophically point of view, this new approaches seek to significantly upgrade and enhance the decision-making process of the tactical commanders.

Multi-Criteria Decision Analysis in Planning of Asbestos-Containing Waste Management

Environmental decision making, particularly about hazardous waste management, is inherently exposed to a high potential conflict, principally because of the trade-off between sociopolitical, environmental, health and economic factors. The need to plan complex contexts has led to an increasing request for decision analytic techniques as support for the decision process. In this work, alternative systems of asbestos-containing waste management (ACW) in Puglia (Southern Italy) were explored by a multi-criteria decision analysis. In particular, through Analytic Hierarchy Process five alternatives management have been compared and ranked according to their performance and efficiency, taking into account environmental, health and socio-economic aspects. A separated valuation has been performed for different temporal scale. For short period results showed a narrow deviation between the disposal alternatives “mono-material landfill in public quarry" and “dedicate cells in existing landfill", with the best performance of the first one. While for long period “treatment plant to eliminate hazard from asbestos-containing waste" was prevalent, although high energy demand required to achieve the change of crystalline structure. A comparison with results from a participative approach in valuation process might be considered as future development of method application to ACW management.

A Previously Underappreciated Impact on Global Warming caused by the Geometrical and Physical Properties of desert sand

The previous researches focused on the influence of anthropogenic greenhouse gases exerting global warming, but not consider whether desert sand may warm the planet, this could be improved by accounting for sand's physical and geometric properties. Here we show, sand particles (because of their geometry) at the desert surface form an extended surface of up to 1 + π/4 times the planar area of the desert that can contact sunlight, and at shallow depths of the desert form another extended surface of at least 1 + π times the planar area that can contact air. Based on this feature, an enhanced heat exchange system between sunlight, desert sand, and air in the spaces between sand particles could be built up automatically, which can increase capture of solar energy, leading to rapid heating of the sand particles, and then the heating of sand particles will dramatically heat the air between sand particles. The thermodynamics of deserts may thus have contributed to global warming, especially significant to future global warming if the current desertification continues to expand.

Extraction of Craniofacial Landmarks for Preoperative to Intraoperative Registration

This paper presents the automated methods employed for extracting craniofacial landmarks in white light images as part of a registration framework designed to support three neurosurgical procedures. The intraoperative space is characterised by white light stereo imaging while the preoperative plan is performed on CT scans. The registration aims at aligning these two modalities to provide a calibrated environment to enable image-guided solutions. The neurosurgical procedures can then be carried out by mapping the entry and target points from CT space onto the patient-s space. The registration basis adopted consists of natural landmarks (eye corner and ear tragus). A 5mm accuracy is deemed sufficient for these three procedures and the validity of the selected registration basis in achieving this accuracy has been assessed by simulation studies. The registration protocol is briefly described, followed by a presentation of the automated techniques developed for the extraction of the craniofacial features and results obtained from tests on the AR and FERET databases. Since the three targeted neurosurgical procedures are routinely used for head injury management, the effect of bruised/swollen faces on the automated algorithms is assessed. A user-interactive method is proposed to deal with such unpredictable circumstances.

Joint Use of Factor Analysis (FA) and Data Envelopment Analysis (DEA) for Ranking of Data Envelopment Analysis

This article combines two techniques: data envelopment analysis (DEA) and Factor analysis (FA) to data reduction in decision making units (DMU). Data envelopment analysis (DEA), a popular linear programming technique is useful to rate comparatively operational efficiency of decision making units (DMU) based on their deterministic (not necessarily stochastic) input–output data and factor analysis techniques, have been proposed as data reduction and classification technique, which can be applied in data envelopment analysis (DEA) technique for reduction input – output data. Numerical results reveal that the new approach shows a good consistency in ranking with DEA.

Reflection of Plane Waves at Free Surface of an Initially Stressed Dissipative Medium

The paper discuses the effect of initial stresses on the reflection coefficients of plane waves in a dissipative medium. Basic governing equations are formulated in context of Biot's incremental deformation theory. These governing equations are solved analytically to obtain the dimensional phase velocities of plane waves propagating in plane of symmetry. Closed-form expressions for the reflection coefficients of P and SV waves- incident at the free surface of an initially stressed dissipative medium are obtained. Numerical computations, using these expressions, are carried out for a particular model. Computations made with the results predicted in presence and absence of the initial stresses and the results have been shown graphically. The study shows that the presence of compressive initial stresses increases the velocity of longitudinal wave (P-wave) but diminishes that of transverse wave (SV-wave). Also the numerical results presented indicate that initial stresses and dissipation might affect the reflection coefficients significantly.

Effect of Environmental Conditions on Energy Efficiency of AAC-based Building Envelopes

Calculations of energy efficiency of several AACbased building envelopes under different climatic conditions are presented. As thermal insulating materials, expanded polystyrene and hydrophobic and hydrophilic mineral wools are assumed. The computations are accomplished using computer code HEMOT developed at Department of Materials Engineering, Faculty of Civil Engineering at the Czech Technical University in Prague. The climatic data of Athens, Kazan, Oslo, Prague and Reykjavík are obtained using METEONORM software.

Verification of K-ω SST Turbulence Model for Supersonic Internal Flows

In this work, we try to find the best setting of Computational Fluid Dynamic solver available for the problems in the field of supersonic internal flows. We used the supersonic air-toair ejector to represent the typical problem in focus. There are multiple oblique shock waves, shear layers, boundary layers and normal shock interacting in the supersonic ejector making this device typical in field of supersonic inner flows. Modeling of shocks in general is demanding on the physical model of fluid, because ordinary conservation equation does not conform to real conditions in the near-shock region as found in many works. From these reasons, we decided to take special care about solver setting in this article by means of experimental approach of color Schlieren pictures and pneumatic measurement. Fast pressure transducers were used to measure unsteady static pressure in regimes with normal shock in mixing chamber. Physical behavior of ejector in several regimes is discussed. Best choice of eddy-viscosity setting is discussed on the theoretical base. The final verification of the k-ω SST is done on the base of comparison between experiment and numerical results.