Long-Term Simulation of Digestive Sound Signals by CEPSTRAL Technique

In this study, an investigation over digestive diseases has been done in which the sound acts as a detector medium. Pursue to the preprocessing the extracted signal in cepstrum domain is registered. After classification of digestive diseases, the system selects random samples based on their features and generates the interest nonstationary, long-term signals via inverse transform in cepstral domain which is presented in digital and sonic form as the output. This structure is updatable or on the other word, by receiving a new signal the corresponding disease classification is updated in the feature domain.

Detecting the Nonlinearity in Time Series from Continuous Dynamic Systems Based on Delay Vector Variance Method

Much time series data is generally from continuous dynamic system. Firstly, this paper studies the detection of the nonlinearity of time series from continuous dynamics systems by applying the Phase-randomized surrogate algorithm. Then, the Delay Vector Variance (DVV) method is introduced into nonlinearity test. The results show that under the different sampling conditions, the opposite detection of nonlinearity is obtained via using traditional test statistics methods, which include the third-order autocovariance and the asymmetry due to time reversal. Whereas the DVV method can perform well on determining nonlinear of Lorenz signal. It indicates that the proposed method can describe the continuous dynamics signal effectively.

Classification Algorithms in Human Activity Recognition using Smartphones

Rapid advancement in computing technology brings computers and humans to be seamlessly integrated in future. The emergence of smartphone has driven computing era towards ubiquitous and pervasive computing. Recognizing human activity has garnered a lot of interest and has raised significant researches- concerns in identifying contextual information useful to human activity recognition. Not only unobtrusive to users in daily life, smartphone has embedded built-in sensors that capable to sense contextual information of its users supported with wide range capability of network connections. In this paper, we will discuss the classification algorithms used in smartphone-based human activity. Existing technologies pertaining to smartphone-based researches in human activity recognition will be highlighted and discussed. Our paper will also present our findings and opinions to formulate improvement ideas in current researches- trends. Understanding research trends will enable researchers to have clearer research direction and common vision on latest smartphone-based human activity recognition area.

Development of Variable Stepsize Variable Order Block Method in Divided Difference Form for the Numerical Solution of Delay Differential Equations

This paper considers the development of a two-point predictor-corrector block method for solving delay differential equations. The formulae are represented in divided difference form and the algorithm is implemented in variable stepsize variable order technique. The block method produces two new values at a single integration step. Numerical results are compared with existing methods and it is evident that the block method performs very well. Stability regions of the block method are also investigated.

Effect of Miniature Cracks on the Fracture Strength and Strain of Tensile Armour Wires

Tensile armour wires provide a flexible pipe's resistance to longitudinal stresses. Flexible pipe manufacturers need to know the effect of defects such as scratches and cracks, with dimensions less than 0.2mm which is the limit of the current nondestructive detection technology, on the fracture stress and fracture strain of the wire for quality assurance purposes. Recent research involving the determination of the fracture strength of cracked wires employed laboratory testing and classical fracture mechanics approach using non-standardised fracture mechanics specimens because standard test specimens could not be manufactured from the wires owing to their sizes. In this work, the effect of miniature cracks on the fracture properties of tensile armour wires was investigated using laboratory and finite element tensile testing simulations with the phenomenological shear fracture model. The investigation revealed that the presence of cracks shallower than 0.2mm is worse on the fracture strain of the wire.

Promoting Mathematical Understanding Using ICT in Teaching and Learning

Information and Communication Technologies (ICT) in mathematical education is a very active field of research and innovation, where learning is understood to be meaningful and grasping multiple linked representation rather than rote memorization, a great amount of literature offering a wide range of theories, learning approaches, methodologies and interpretations, are generally stressing the potentialities for teaching and learning using ICT. Despite the utilization of new learning approaches with ICT, students experience difficulties in learning concepts relevant to understanding mathematics, much remains unclear about the relationship between the computer environment, the activities it might support, and the knowledge that might emerge from such activities. Many questions that might arise in this regard: to what extent does the use of ICT help students in the process of understanding and solving tasks or problems? Is it possible to identify what aspects or features of students' mathematical learning can be enhanced by the use of technology? This paper will highlight the interest of the integration of information and communication technologies (ICT) into the teaching and learning of mathematics (quadratic functions), it aims to investigate the effect of four instructional methods on students- mathematical understanding and problem solving. Quantitative and qualitative methods are used to report about 43 students in middle school. Results showed that mathematical thinking and problem solving evolves as students engage with ICT activities and learn cooperatively.

Design of Digital Differentiator to Optimize Relative Error

It is observed that the Weighted least-square (WLS) technique, including the modifications, results in equiripple error curve. The resultant error as a percent of the ideal value is highly non-uniformly distributed over the range of frequencies for which the differentiator is designed. The present paper proposes a modification to the technique so that the optimization procedure results in lower maximum relative error compared to the ideal values. Simulation results for first order as well as higher order differentiators are given to illustrate the excellent performance of the proposed method.

Development of an Infrared Thermography Method with CO2 Laser Excitation, Applied to Defect Detection in CFRP

This paper presents a NDT by infrared thermography with excitation CO2 Laser, wavelength of 10.6 μm. This excitation is the controllable heating beam, confirmed by a preliminary test on a wooden plate 1.2 m x 0.9 m x 1 cm. As the first practice, this method is applied to detecting the defect in CFRP heated by the Laser 300 W during 40 s. Two samples 40 cm x 40 cm x 4.5 cm are prepared, one with defect, another one without defect. The laser beam passes through the lens of a deviation device, and heats the samples placed at a determinate position and area. As a result, the absence of adhesive can be detected. This method displays prominently its application as NDT with the composite materials. This work gives a good perspective to characterize the laser beam, which is very useful for the next detection campaigns.

Regulatory Effects of Carbon Sources on Tabtoxin Production (A β-lactam Phytotoxin of Pseudomonas syringae pv. tabaci)

The effects of divers carbon substrates were investigated for the tabtoxin production of an isolated pathogenic Pseudomonas syringae pv. tabaci, the causal agent of wildfire of tobacco and are discussed in relation to the bacterium growth. The isolated organism was grown in batch culture on Woolley's medium (28°C, 200 rpm, during 5 days). The growth has been measured by the optical density (OD) at 620 nm and the tabtoxin production quantified by Escherichia coli (K-12) bioassay technique. The growth and the tabtoxin production were both influenced by the substrates (sugars, amino acids, organic acids) used, each, as a sole carbon source and as a supplement for the same amino acids. The most significant quantities of tabtoxin were obtained in presence of some amino acids used as sole carbon source and/or as supplement.

Real Power Generation Scheduling to Improve Steady State Stability Limit in the Java-Bali 500kV Interconnection Power System

This paper will discuss about an active power generator scheduling method in order to increase the limit level of steady state systems. Some power generator optimization methods such as Langrange, PLN (Indonesian electricity company) Operation, and the proposed Z-Thevenin-based method will be studied and compared in respect of their steady state aspects. A method proposed in this paper is built upon the thevenin equivalent impedance values between each load respected to each generator. The steady state stability index obtained with the REI DIMO method. This research will review the 500kV-Jawa-Bali interconnection system. The simulation results show that the proposed method has the highest limit level of steady state stability compared to other optimization techniques such as Lagrange, and PLN operation. Thus, the proposed method can be used to create the steady state stability limit of the system especially in the peak load condition.

Cloud Computing: Changing Cogitation about Computing

Cloud Computing is a new technology that helps us to use the Cloud for compliance our computation needs. Cloud refers to a scalable network of computers that work together like Internet. An important element in Cloud Computing is that we shift processing, managing, storing and implementing our data from, locality into the Cloud; So it helps us to improve the efficiency. Because of it is new technology, it has both advantages and disadvantages that are scrutinized in this article. Then some vanguards of this technology are studied. Afterwards we find out that Cloud Computing will have important roles in our tomorrow life!

Evaluation of State of the Art IDS Message Exchange Protocols

During the last couple of years, the degree of dependence on IT systems has reached a dimension nobody imagined to be possible 10 years ago. The increased usage of mobile devices (e.g., smart phones), wireless sensor networks and embedded devices (Internet of Things) are only some examples of the dependency of modern societies on cyber space. At the same time, the complexity of IT applications, e.g., because of the increasing use of cloud computing, is rising continuously. Along with this, the threats to IT security have increased both quantitatively and qualitatively, as recent examples like STUXNET or the supposed cyber attack on Illinois water system are proofing impressively. Once isolated control systems are nowadays often publicly available - a fact that has never been intended by the developers. Threats to IT systems don’t care about areas of responsibility. Especially with regard to Cyber Warfare, IT threats are no longer limited to company or industry boundaries, administrative jurisdictions or state boundaries. One of the important countermeasures is increased cooperation among the participants especially in the field of Cyber Defence. Besides political and legal challenges, there are technical ones as well. A better, at least partially automated exchange of information is essential to (i) enable sophisticated situational awareness and to (ii) counter the attacker in a coordinated way. Therefore, this publication performs an evaluation of state of the art Intrusion Detection Message Exchange protocols in order to guarantee a secure information exchange between different entities.

Software Maintenance Severity Prediction for Object Oriented Systems

As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done in time especially for the critical applications. As, Neural networks, which have been already applied in software engineering applications to build reliability growth models predict the gross change or reusability metrics. Neural networks are non-linear sophisticated modeling techniques that are able to model complex functions. Neural network techniques are used when exact nature of input and outputs is not known. A key feature is that they learn the relationship between input and output through training. In this present work, various Neural Network Based techniques are explored and comparative analysis is performed for the prediction of level of need of maintenance by predicting level severity of faults present in NASA-s public domain defect dataset. The comparison of different algorithms is made on the basis of Mean Absolute Error, Root Mean Square Error and Accuracy Values. It is concluded that Generalized Regression Networks is the best algorithm for classification of the software components into different level of severity of impact of the faults. The algorithm can be used to develop model that can be used for identifying modules that are heavily affected by the faults.

Multi-Agents Coordination Model in Inter- Organizational Workflow: Applying in Egovernment

Inter-organizational Workflow (IOW) is commonly used to support the collaboration between heterogeneous and distributed business processes of different autonomous organizations in order to achieve a common goal. E-government is considered as an application field of IOW. The coordination of the different organizations is the fundamental problem in IOW and remains the major cause of failure in e-government projects. In this paper, we introduce a new coordination model for IOW that improves the collaboration between government administrations and that respects IOW requirements applied to e-government. For this purpose, we adopt a Multi-Agent approach, which deals more easily with interorganizational digital government characteristics: distribution, heterogeneity and autonomy. Our model integrates also different technologies to deal with the semantic and technologic interoperability. Moreover, it conserves the existing systems of government administrations by offering a distributed coordination based on interfaces communication. This is especially applied in developing countries, where administrations are not necessary equipped with workflow systems. The use of our coordination techniques allows an easier migration for an e-government solution and with a lower cost. To illustrate the applicability of the proposed model, we present a case study of an identity card creation in Tunisia.

Application of Artificial Neural Networks for Temperature Forecasting

In this paper, the application of neural networks to study the design of short-term temperature forecasting (STTF) Systems for Kermanshah city, west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STTF systems is used. Our study based on MLP was trained and tested using ten years (1996-2006) meteorological data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STTF systems.

Low Voltage Squarer Using Floating Gate MOSFETs

A new low-voltage floating gate MOSFET (FGMOS) based squarer using square law characteristic of the FGMOS is proposed in this paper. The major advantages of the squarer are simplicity, rail-to-rail input dynamic range, low total harmonic distortion, and low power consumption. The proposed circuit is biased without body effect. The circuit is designed and simulated using SPICE in 0.25μm CMOS technology. The squarer is operated at the supply voltages of ±0.75V . The total harmonic distortion (THD) for the input signal 0.75Vpp at 25 KHz, and maximum power consumption were found to be less than 1% and 319μW respectively.

Interactive Model Based On an Extended CPN

The UML modeling of complex distributed systems often is a great challenge due to the large amount of parallel real-time operating components. In this paper the problems of verification of such systems are discussed. ECPN, an Extended Colored Petri Net is defined to formally describe state transitions of components and interactions among components. The relationship between sequence diagrams and Free Choice Petri Nets is investigated. Free Choice Petri Net theory helps verifying the liveness of sequence diagrams. By converting sequence diagrams to ECPNs and then comparing behaviors of sequence diagram ECPNs and statecharts, the consistency among models is analyzed. Finally, a verification process for an example model is demonstrated.

A Consistency Protocol Multi-Layer for Replicas Management in Large Scale Systems

Large scale systems such as computational Grid is a distributed computing infrastructure that can provide globally available network resources. The evolution of information processing systems in Data Grid is characterized by a strong decentralization of data in several fields whose objective is to ensure the availability and the reliability of the data in the reason to provide a fault tolerance and scalability, which cannot be possible only with the use of the techniques of replication. Unfortunately the use of these techniques has a height cost, because it is necessary to maintain consistency between the distributed data. Nevertheless, to agree to live with certain imperfections can improve the performance of the system by improving competition. In this paper, we propose a multi-layer protocol combining the pessimistic and optimistic approaches conceived for the data consistency maintenance in large scale systems. Our approach is based on a hierarchical representation model with tree layers, whose objective is with double vocation, because it initially makes it possible to reduce response times compared to completely pessimistic approach and it the second time to improve the quality of service compared to an optimistic approach.

Efficient Spectral Analysis of Quasi Stationary Time Series

Power Spectral Density (PSD) of quasi-stationary processes can be efficiently estimated using the short time Fourier series (STFT). In this paper, an algorithm has been proposed that computes the PSD of quasi-stationary process efficiently using offline autoregressive model order estimation algorithm, recursive parameter estimation technique and modified sliding window discrete Fourier Transform algorithm. The main difference in this algorithm and STFT is that the sliding window (SW) and window for spectral estimation (WSA) are separately defined. WSA is updated and its PSD is computed only when change in statistics is detected in the SW. The computational complexity of the proposed algorithm is found to be lesser than that for standard STFT technique.

Incorporation Mechanism of Stabilizing Simulated Lead-Laden Sludge in Aluminum-Rich Ceramics

This study investigated a strategy of blending lead-laden sludge and Al-rich precursors to reduce the release of metals from the stabilized products. Using PbO as the simulated lead-laden sludge to sinter with γ-Al2O3 by Pb:Al molar ratios of 1:2 and 1:12, PbAl2O4 and PbAl12O19 were formed as final products during the sintering process, respectively. By firing the PbO + γ-Al2O3 mixtures with different Pb/Al molar ratios at 600 to 1000 °C, the lead transformation was determined through X-ray diffraction (XRD) data. In Pb/Al molar ratio of 1/2 system, the formation of PbAl2O4 is initiated at 700 °C, but an effective formation was observed above 750 °C. An intermediate phase, Pb9Al8O21, was detected in the temperature range of 800-900 °C. However, different incorporation behavior for sintering PbO with Al-rich precursors at a Pb/Al molar ratio of 1/12 was observed during the formation of PbAl12O19 in this system. In the sintering process, both temperature and time effect on the formation of PbAl2O4 and PbAl12O19 phases were estimated. Finally, a prolonged leaching test modified from the U.S. Environmental Protection Agency-s toxicity characteristic leaching procedure (TCLP) was used to evaluate the durability of PbO, Pb9Al8O21, PbAl2O4 and PbAl12O19 phases. Comparison for the leaching results of the four phases demonstrated the higher intrinsic resistance of PbAl12O19 against acid attack.