A Trainable Neural Network Ensemble for ECG Beat Classification

This paper illustrates the use of a combined neural network model for classification of electrocardiogram (ECG) beats. We present a trainable neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. We process a three stage technique for detection of premature ventricular contraction (PVC) from normal beats and other heart diseases. This method includes a denoising, a feature extraction and a classification. At first we investigate the application of stationary wavelet transform (SWT) for noise reduction of the electrocardiogram (ECG) signals. Then feature extraction module extracts 10 ECG morphological features and one timing interval feature. Then a number of multilayer perceptrons (MLPs) neural networks with different topologies are designed. The performance of the different combination methods as well as the efficiency of the whole system is presented. Among them, Stacked Generalization as a proposed trainable combined neural network model possesses the highest recognition rate of around 95%. Therefore, this network proves to be a suitable candidate in ECG signal diagnosis systems. ECG samples attributing to the different ECG beat types were extracted from the MIT-BIH arrhythmia database for the study.

DEMO Based Optimal Power Purchase Planning Under Electricity Price Uncertainty

Due to the deregulation of the Electric Supply Industry and the resulting emergence of electricity market, the volumes of power purchases are on the rise all over the world. In a bid to meet the customer-s demand in a reliable and yet economic manner, utilities purchase power from the energy market over and above its own production. This paper aims at developing an optimal power purchase model with two objectives viz economy and environment ,taking various functional operating constraints such as branch flow limits, load bus voltage magnitudes limits, unit capacity constraints and security constraints into consideration.The price of purchased power being an uncertain variable is modeled using fuzzy logic. DEMO (Differential Evolution For Multi-objective Optimization) is used to obtain the pareto-optimal solution set of the multi-objective problem formulated. Fuzzy set theory has been employed to extract the best compromise non-dominated solution. The results obtained on IEEE 30 bus system are presented and compared with that of NSGAII.

Modeling of Session Initiation Protocol Invite Transaction using Colored Petri Nets

Wireless mobile communications have experienced the phenomenal growth through last decades. The advances in wireless mobile technologies have brought about a demand for high quality multimedia applications and services. For such applications and services to work, signaling protocol is required for establishing, maintaining and tearing down multimedia sessions. The Session Initiation Protocol (SIP) is an application layer signaling protocols, based on request/response transaction model. This paper considers SIP INVITE transaction over an unreliable medium, since it has been recently modified in Request for Comments (RFC) 6026. In order to help in assuring that the functional correctness of this modification is achieved, the SIP INVITE transaction is modeled and analyzed using Colored Petri Nets (CPNs). Based on the model analysis, it is concluded that the SIP INVITE transaction is free of livelocks and dead codes, and in the same time it has both desirable and undesirable deadlocks. Therefore, SIP INVITE transaction should be subjected for additional updates in order to eliminate undesirable deadlocks. In order to reduce the cost of implementation and maintenance of SIP, additional remodeling of the SIP INVITE transaction is recommended.

Complex Energy Signal Model for Digital Human Fingerprint Matching

This paper describes a complex energy signal model that is isomorphic with digital human fingerprint images. By using signal models, the problem of fingerprint matching is transformed into the signal processing problem of finding a correlation between two complex signals that differ by phase-rotation and time-scaling. A technique for minutiae matching that is independent of image translation, rotation and linear-scaling, and is resistant to missing minutiae is proposed. The method was tested using random data points. The results show that for matching prints the scaling and rotation angles are closely estimated and a stronger match will have a higher correlation.

A Ring-Shaped Tri-Axial Force Sensor for Minimally Invasive Surgery

This paper presents the design of a ring-shaped tri-axial fore sensor that can be incorporated into the tip of a guidewire for use in minimally invasive surgery (MIS). The designed sensor comprises a ring-shaped structure located at the center of four cantilever beams. The ringdesign allows surgical tools to be easily passed through which largely simplified the integration process. Silicon nanowires (SiNWs) are used aspiezoresistive sensing elementsembeddedon the four cantilevers of the sensor to detect the resistance change caused by the applied load.An integration scheme with new designed guidewire tip structure having two coils at the distal end is presented. Finite element modeling has been employed in the sensor design to find the maximum stress location in order to put the SiNWs at the high stress regions to obtain maximum output. A maximum applicable force of 5 mN is found from modeling. The interaction mechanism between the designed sensor and a steel wire has been modeled by FEM. A linear relationship between the applied load on the steel wire and the induced stress on the SiNWs were observed.

Design of an M-Channel Cosine Modulated Filter Bank by New Cosh Window Based FIR Filters

In this paper newly reported Cosh window function is used in the design of prototype filter for M-channel Near Perfect Reconstruction (NPR) Cosine Modulated Filter Bank (CMFB). Local search optimization algorithm is used for minimization of distortion parameters by optimizing the filter coefficients of prototype filter. Design examples are presented and comparison has been made with Kaiser window based filterbank design of recently reported work. The result shows that the proposed design approach provides lower distortion parameters and improved far-end suppression than the Kaiser window based design of recent reported work.

SLM Using Riemann Sequence Combined with DCT Transform for PAPR Reduction in OFDM Communication Systems

Orthogonal Frequency Division Multiplexing (OFDM) is an efficient method of data transmission for high speed communication systems. However, the main drawback of OFDM systems is that, it suffers from the problem of high Peak-to-Average Power Ratio (PAPR) which causes inefficient use of the High Power Amplifier and could limit transmission efficiency. OFDM consist of large number of independent subcarriers, as a result of which the amplitude of such a signal can have high peak values. In this paper, we propose an effective reduction scheme that combines DCT and SLM techniques. The scheme is composed of the DCT followed by the SLM using the Riemann matrix to obtain phase sequences for the SLM technique. The simulation results show PAPR can be greatly reduced by applying the proposed scheme. In comparison with OFDM, while OFDM had high values of PAPR –about 10.4dB our proposed method achieved about 4.7dB reduction of the PAPR with low complexities computation. This approach also avoids randomness in phase sequence selection, which makes it simpler to decode at the receiver. As an added benefit, the matrices can be generated at the receiver end to obtain the data signal and hence it is not required to transmit side information (SI).

Pyrolysis of Rice Husk in a Fixed Bed Reactor

Fixed-bed slow pyrolysis experiments of rice husk have been conducted to determine the effect of pyrolysis temperature, heating rate, particle size and reactor length on the pyrolysis product yields. Pyrolysis experiments were performed at pyrolysis temperature between 400 and 600°C with a constant heating rate of 60°C/min and particle sizes of 0.60-1.18 mm. The optimum process conditions for maximum liquid yield from the rice husk pyrolysis in a fixed bed reactor were also identified. The highest liquid yield was obtained at a pyrolysis temperature of 500°C, particle size of 1.18-1.80 mm, with a heating rate of 60°C/min in a 300 mm length reactor. The obtained yield of, liquid, gas and solid were found be in the range of 22.57-31.78 %, 27.75-42.26 % and 34.17-42.52 % (all weight basics) respectively at different pyrolysis conditions. The results indicate that the effects of pyrolysis temperature and particle size on the pyrolysis yield are more significant than that of heating rate and reactor length. The functional groups and chemical compositions present in the liquid obtained at optimum conditions were identified by Fourier Transform-Infrared (FT-IR) spectroscopy and Gas Chromatography/ Mass Spectroscopy (GC/MS) analysis respectively.

Factors Influence Depositors- Withdrawal Behavior in Islamic Banks: A Theory of Reasoned Action

Unlike its conventional counterpart, Islamic principles forbid Islamic banks to take any interest-related income and thus makes deposits from depositors as an important source of fund for its operational and financing. Consequently, the risk of deposit withdrawal by depositors is an important aspect that should be wellmanaged in Islamic banking. This paper aims to investigate factors that influence depositors- withdrawal behavior in Islamic banks, particularly in Malaysia, using the framework of theory of reasoned action. A total of 368 respondents from Klang valley are involved in the analysis. The paper finds that all the constructs variable i.e. normative beliefs, subjective norms, behavioral beliefs, and attitude towards behavior are perceived to be distinct by the respondents. In addition, the structural equation model is able to verify the structural relationships between subjective norms, attitude towards behavior and behavioral intention. Subjective norms gives more influence to depositors- decision on deposit withdrawal compared to attitude towards behavior.

Resource Discovery in Web-Services Based Grids

A Web-services based grid infrastructure is evolving to be readily available in the near future. In this approach, the Web services are inherited (encapsulated or functioned) into the same existing Grid services class. In practice there is not much difference between the existing Web and grid infrastructure. Grid services emerged as stateful web services. In this paper, we present the key components of web-services based grid and also how the resource discovery is performed on web-services based grid considering resource discovery, as a critical service, to be provided by any type of grid.

The Advantages of Integration for Social Systems – Evidence from the Automobile Industry

The Japanese integrative approach to social systems can be observed in supply chain management as well as in the relationship between public and private sectors. Both the Lean Production System and the Developmental State Model are characterized by efforts towards the achievement of mutual goals, resulting in initiatives for capacity building which emphasize the system level. In Brazil, although organizations undertake efforts to build capabilities at the individual and organizational levels, the system level is being neglected. Fieldwork data confirmed the findings of other studies in terms of the lack of integration in supply chain management in the Brazilian automobile industry. Moreover, due to the absence of an active role of the Brazilian state in its relationship with the private sector, automakers are not fully exploiting the opportunities in the domestic and regional markets. For promoting a higher level of economic growth as well as to increase the degree of spill-over of technologies and techniques, a more integrative approach is needed.

Emotion Classification by Incremental Association Language Features

The Major Depressive Disorder has been a burden of medical expense in Taiwan as well as the situation around the world. Major Depressive Disorder can be defined into different categories by previous human activities. According to machine learning, we can classify emotion in correct textual language in advance. It can help medical diagnosis to recognize the variance in Major Depressive Disorder automatically. Association language incremental is the characteristic and relationship that can discovery words in sentence. There is an overlapping-category problem for classification. In this paper, we would like to improve the performance in classification in principle of no overlapping-category problems. We present an approach that to discovery words in sentence and it can find in high frequency in the same time and can-t overlap in each category, called Association Language Features by its Category (ALFC). Experimental results show that ALFC distinguish well in Major Depressive Disorder and have better performance. We also compare the approach with baseline and mutual information that use single words alone or correlation measure.

Scenarios of Societal Security and Business Continuity Cycles

Societal security, continuity scenarios and methodological cycling approach explained in this article. Namely societal security organizational challenges ask implementation of international standards BS 25999-2 & global ISO 22300 which is a family of standards for business continuity management system. Efficient global organization system is distinguished of high entity´s complexity, connectivity & interoperability, having not only cooperative relations in a fact. Competing business have numerous participating ´enemies´, which are in apparent or hidden opponent and antagonistic roles with prosperous organization system, resulting to a crisis scene or even to a battle theatre. Organization business continuity scenarios are necessary for such ´a play´ preparedness, planning, management & overmastering in real environments.

A Dual Model for Efficiency Evaluation Considering Time Lag Effect

A DEA model can generally evaluate the performance using multiple inputs and outputs for the same period. However, it is hard to avoid the production lead time phenomenon some times, such as long-term project or marketing activity. A couple of models have been suggested to capture this time lag issue in the context of DEA. This paper develops a dual-MPO model to deal with time lag effect in evaluating efficiency. A numerical example is also given to show that the proposed model can be used to get efficiency and reference set of inefficient DMUs and to obtain projected target value of input attributes for inefficient DMUs to be efficient.

Research on Transformer Condition-based Maintenance System using the Method of Fuzzy Comprehensive Evaluation

This study adopted previous fault patterns, results of detection analysis, historical records and data, and experts- experiences to establish fuzzy principles and estimate the failure probability index of components of a power transformer. Considering that actual parameters and limiting conditions of parameters may differ, this study used the standard data of IEC, IEEE, and CIGRE as condition parameters. According to the characteristics of each condition parameter, relative degradation was introduced to reflect the degree of influence of the factors on the transformer condition. The method of fuzzy mathematics was adopted to determine the subordinate function of the transformer condition. The calculation used the Matlab Fuzzy Tool Box to select the condition parameters of coil winding, iron core, bushing, OLTC, insulating oil and other auxiliary components and factors (e.g., load records, performance history, and maintenance records) of the transformer to establish the fuzzy principles. Examples were presented to support the rationality and effectiveness of the evaluation method of power transformer performance conditions, as based on fuzzy comprehensive evaluation.

Piezoelectric Polarization Effect on Debye Frequency and Temperature in Nitride Wurtzites

We have investigated the effect of piezoelectric (PZ) polarization property in binary as well as in ternary wurtzite nitrides. It is found that with the presence of PZ polarization property, the phonon group velocity is modified. The change in phonon group velocity due to PZ polarization effect directly depends on piezoelectric tensor value. Using different piezoelectric tensor values recommended by different workers in the literature, percent change in group velocities of phonons has been estimated. The Debye temperatures and frequencies of binary nitrides GaN, AlN and InN are also calculated using the modified group velocities. For ternary nitrides AlxGa(1-x)N, InxGa(1-x)N and InxAl(1-x)N, the phonon group velocities have been calculated as a functions of composition. A small positive bowing is observed in phonon group velocities of ternary alloys. Percent variations in phonon group velocities are also calculated for a straightforward comparison among ternary nitrides. The results are expected to show a change in phonon relaxation rates and thermal conductivity of III-nitrides when piezoelectric polarization property is taken into consideration.

Analytic and Finite Element Solutions for Temperature Profiles in Welding using Varied Heat Source Models

Solutions for the temperature profile around a moving heat source are obtained using both analytic and finite element (FEM) methods. Analytic and FEM solutions are applied to study the temperature profile in welding. A moving heat source is represented using both point heat source and uniform distributed disc heat source models. Analytic solutions are obtained by solving the partial differential equation for energy conservation in a solid, and FEM results are provided by simulating welding using the ANSYS software. Comparison is made for quasi steady state conditions. The results provided by the analytic solutions are in good agreement with results obtained by FEM.

Study of γ Irradiation and Storage Time on Microbial Load and Chemical Quality of Persian Saffron

Irradiation is considered one of the most efficient technological processes for the reduction of microorganisms in food. It can be used to improve the safety of food products, and to extend their shelf lives. The aim of this study was to evaluate the effects of gamma irradiation for improvement of saffron shelf life. Samples were treated with 0 (none irradiated), 1.0, 2.0, 3.0 and 4.0 kGy of gamma irradiation and held for 2 months. The control and irradiated samples were underwent microbial analysis, chemical characteristics and sensory evaluation at 30 days intervals. Microbial analysis indicated that irradiation had a significant effect (P < 0.05) on the reduction of microbial loads. There was no significant difference in sensory quality and chemical characteristics during storage in saffron.

An Assessment of Ozone Levels in Typical Urban Areas in the Malaysian Peninsular

Air quality studies were carried out in the towns of Putrajaya, Petaling Jaya and Nilai in the Malaysian Peninsular. In this study, the variations of Ozone (O3) concentrations over a four year period (2008-2011) were investigated using data obtained from the Malaysian Department of the Environment (DOE). This study aims to identify and describe the daily and monthly variations of O3 concentrations at the monitoring sites mentioned. The SPPS program (Statistical Package for the Social Science) was used to analyze this data in order to obtain the variations of O3 and also to clarify the relationship between the stations. The findings of the study revealed that the highest concentration of O3 occurred during the midday and afternoon (between 13:00-15:00 hrs). The comparison between stations also showed that highest O3 concentrations were recorded in Putrajaya. The comparisons of average and maximum concentrations of O3 for the three stations showed that the strongest significant correlation was recorded in the Petaling Jaya station with the value R2= 0.667. Results from this study indicate that in the urban areas of Peninsular Malaysia, the concentration of O3 depends on the concentration of NOx. Furthermore, HYSPLIT back trajectories (-72h) indicated that air-mass transport patterns can also influence the O3 concentration in the areas studied.

Investigation of Water Deficit Stress on Agronomical Traits of Soybean Cultivars in Temperate Climate

In order to investigate water deficit stress on 24 of soybean (Glycine Max. L) cultivars and lines in temperate climate, an experiment was conducted in Iran Seed and Plant Improvement Institute. Stress levels were irrigation after evaporation of 50, 100, 150 mm water from pan, class A. Randomized Completely Block Design was arranged for each stress levels. Some traits such as, node number, plant height, pod number per area, grain number per pod, grain number per area, 1000 grains weight, grain yield and harvest index were measured. Results showed that water deficit stress had significant effect on node number, plant height, pod number per area, grain number per pod, grain number per area, 1000 grains weight and harvest index. Also all of agronomic traits except harvest index influenced significantly by cultivars and lines. The least and most grain yield was belonged to Ronak X Williams and M41 x Clark respectively.