Good Practices in the Development of the Erasmus Mundus Master program in Color in Informatics and Media Technology

The main objective of this paper is to identify and disseminate good practice in quality assurance and enhancement as well as in teaching and learning at master level. This paper focuses on the experience of the Erasmus Mundus Master program CIMET (Color in Informatics and Media Technology). Amongst topics covered, we discuss the adjustments necessary to a curriculum designed for excellent international students and their preparation for a global labor market.

Measurement of I-V Characteristics of a PtSi/p-Si Schottky Barrier Diode at low Temperatures

The current-voltage characteristics of a PtSi/p-Si Schottky barrier diode was measured at the temperature of 85 K and from the forward bias region of the I-V curve, the electrical parameters of the diode were measured by three methods. The results obtained from the two methods which considered the series resistance were in close agreement with each other and from them barrier height (), ideality factor (n) and series resistance () were found to be 0.2045 eV, 2.877 and 14.556 K respectively. By measuring the I-V characteristics in the temperature range of 85-136 K the electrical parameters were observed to have strong dependency on temperature. The increase of barrier height and decrease of ideality factor with increasing temperature is attributed to the existence of barrier height inhomogeneities in the silicide-semiconductor structure.

Temperature Effect on the Organic Solar Cells Parameters

In this work, the influence of temperature on the different parameters of solar cells based on organic semiconductors are studied. The short circuit current Isc increases so monotonous with temperature and then saturates to a maximum value before decreasing at high temperatures. The open circuit voltage Vco decreases linearly with temperature. The fill factor FF and efficiency, which are directly related with Isc and Vco follow the variations of the letters. The phenomena are explained by the behaviour of the mobility which is a temperature activated process.

Analytical Prediction of Seismic Response of Steel Frames with Superelastic Shape Memory Alloy

Superelastic Shape Memory Alloy (SMA) is accepted when it used as connection in steel structures. The seismic behaviour of steel frames with SMA is being assessed in this study. Three eightstorey steel frames with different SMA systems are suggested, the first one of which is braced with diagonal bracing system, the second one is braced with nee bracing system while the last one is which the SMA is used as connection at the plastic hinge regions of beams. Nonlinear time history analyses of steel frames with SMA subjected to two different ground motion records have been performed using Seismostruct software. To evaluate the efficiency of suggested systems, the dynamic responses of the frames were compared. From the comparison results, it can be concluded that using SMA element is an effective way to improve the dynamic response of structures subjected to earthquake excitations. Implementing the SMA braces can lead to a reduction in residual roof displacement. The shape memory alloy is effective in reducing the maximum displacement at the frame top and it provides a large elastic deformation range. SMA connections are very effective in dissipating energy and reducing the total input energy of the whole frame under severe seismic ground motion. Using of the SMA connection system is more effective in controlling the reaction forces at the base frame than other bracing systems. Using SMA as bracing is more effective in reducing the displacements. The efficiency of SMA is dependant on the input wave motions and the construction system as well.

Method of Moments Applied to a Cuboidal Cavity Resonator: Effect of Gravitational Field Produced by a Black Hole

This paper deals with the formulation of Maxwell-s equations in a cavity resonator in the presence of the gravitational field produced by a blackhole. The metric of space-time due to the blackhole is the Schwarzchild metric. Conventionally, this is expressed in spherical polar coordinates. In order to adapt this metric to our problem, we have considered this metric in a small region close to the blackhole and expressed this metric in a cartesian system locally.

Behavioral Signature Generation using Shadow Honeypot

A novel behavioral detection framework is proposed to detect zero day buffer overflow vulnerabilities (based on network behavioral signatures) using zero-day exploits, instead of the signature-based or anomaly-based detection solutions currently available for IDPS techniques. At first we present the detection model that uses shadow honeypot. Our system is used for the online processing of network attacks and generating a behavior detection profile. The detection profile represents the dataset of 112 types of metrics describing the exact behavior of malware in the network. In this paper we present the examples of generating behavioral signatures for two attacks – a buffer overflow exploit on FTP server and well known Conficker worm. We demonstrated the visualization of important aspects by showing the differences between valid behavior and the attacks. Based on these metrics we can detect attacks with a very high probability of success, the process of detection is however very expensive.

Evaluation of the Energy Consumption per Bit inBENES Optical Packet Switch

We evaluate the average energy consumption per bit in Optical Packet Switches equipped with BENES switching fabric realized in Semiconductor Optical Amplifier (SOA) technology. We also study the impact that the Amplifier Spontaneous Emission (ASE) noise generated by a transmission system has on the power consumption of the BENES switches due to the gain saturation of the SOAs used to realize the switching fabric. As a matter of example for 32×32 switches supporting 64 wavelengths and offered traffic equal to 0,8, the average energy consumption per bit is 2, 34 · 10-1 nJ/bit and increases if ASE noise introduced by the transmission systems is increased.

Torque Based Selection of ANN for Fault Diagnosis of Wound Rotor Asynchronous Motor-Converter Association

In this paper, an automatic system of diagnosis was developed to detect and locate in real time the defects of the wound rotor asynchronous machine associated to electronic converter. For this purpose, we have treated the signals of the measured parameters (current and speed) to use them firstly, as indicating variables of the machine defects under study and, secondly, as inputs to the Artificial Neuron Network (ANN) for their classification in order to detect the defect type in progress. Once a defect is detected, the interpretation system of information will give the type of the defect and its place of appearance.

Design of a Carbon Silicon Electrode for Iontophoresis Treatment towards Alopecia

This study presents design of a carbon silicon electrode for iontophorsis treatment towards alopecia. The alopecia is a medical description means loss of hair from the body. For solving this problem, the drug need to be delivered into the scalp, therefore, the iontophoresis was chosen to use in this treatment. However, almost common electrodes of iontophoresis device are made with metal material, the electrodes could give patients hurt when they using it, and it is hard to avoid the hair for attaching the hair. For this reason, an electrode is made with silicon material to decrease the hurt from the electrodes, and the carbon material is mixed in it for increasing conductance. The several cones with stainless material on the electrode make the electrode is able to void hair to attach the affected part. According to the results of a vivo-experiment, the carbon silicon electrode showed a good performance and in treatment comfortably.

A Frugal Bidding Procedure for Replicating WWW Content

Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.

A Study of Calcination and Carbonation of Cockle Shell

Calcium oxide (CaO) as carbon dioxide (CO2) adsorbent at the elevated temperature has been very well-received thus far. The CaO can be synthesized from natural calcium carbonate (CaCO3) sources through the reversible calcination-carbonation process. In the study, cockle shell has been selected as CaO precursors. The objectives of the study are to investigate the performance of calcination and carbonation with respect to different temperature, heating rate, particle size and the duration time. Overall, better performance is shown at the calcination temperature of 850oC for 40 minutes, heating rate of 20oC/min, particle size of < 0.125mm and the carbonation temperature is at 650oC. The synthesized materials have been characterized by nitrogen physisorption and surface morphology analysis. The effectiveness of the synthesized cockle shell in capturing CO2 (0.72 kg CO2/kg adsorbent) which is comparable to the commercialized adsorbent (0.60 kg CO2/kg adsorbent) makes them as the most promising materials for CO2 capture.

Applications of Prediction and Identification Using Adaptive DCMAC Neural Networks

An adaptive dynamic cerebellar model articulation controller (DCMAC) neural network used for solving the prediction and identification problem is proposed in this paper. The proposed DCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) neural network in efficient learning mechanism, guaranteed system stability and dynamic response. The recurrent network is embedded in the DCMAC by adding feedback connections in the association memory space so that the DCMAC captures the dynamic response, where the feedback units act as memory elements. The dynamic gradient descent method is adopted to adjust DCMAC parameters on-line. Moreover, the analytical method based on a Lyapunov function is proposed to determine the learning-rates of DCMAC so that the variable optimal learning-rates are derived to achieve most rapid convergence of identifying error. Finally, the adaptive DCMAC is applied in two computer simulations. Simulation results show that accurate identifying response and superior dynamic performance can be obtained because of the powerful on-line learning capability of the proposed DCMAC.

Signal Reconstruction Using Cepstrum of Higher Order Statistics

This paper presents an algorithm for reconstructing phase and magnitude responses of the impulse response when only the output data are available. The system is driven by a zero-mean independent identically distributed (i.i.d) non-Gaussian sequence that is not observed. The additive noise is assumed to be Gaussian. This is an important and essential problem in many practical applications of various science and engineering areas such as biomedical, seismic, and speech processing signals. The method is based on evaluating the bicepstrum of the third-order statistics of the observed output data. Simulations results are presented that demonstrate the performance of this method.

Temperature Effect on the Mechanical Properties of Pd3Rh and PdRh3 Ordered Alloys

The aim of this research was to calculate the mechanical properties of Pd3Rh and PdRh3 ordered alloys. The molecular dynamics (MD) simulation technique was used to obtain temperature dependence of the energy, the Yong modulus, the shear modulus, the bulk modulus, Poisson-s ratio and the elastic stiffness constants at the isobaric-isothermal (NPT) ensemble in the range of 100-325 K. The interatomic potential energy and force on atoms were calculated by Quantum Sutton-Chen (Q-SC) many body potential. Our MD simulation results show the effect of temperature on the cohesive energy and mechanical properties of Pd3Rh as well as PdRh3 alloys. Our computed results show good agreement with the experimental results where they have been available.

Comparison between Optimized Passive Vehicle Suspension System and Semi Active Fuzzy Logic Controlled Suspension System Regarding Ride and Handling

The purpose of suspension system in automobiles is to improve the ride comfort and road handling. In this research the ride and handling performance of a specific automobile with passive suspension system is compared to a proposed fuzzy logic semi active suspension system designed for that automobile. The bodysuspension- wheel system is modeled as a two degree of freedom quarter car model. MATLAB/SIMULINK [1] was used for simulation and controller design. The fuzzy logic controller is based on two inputs namely suspension velocity and body velocity. The output of the fuzzy controller is the damping coefficient of the variable damper. The result shows improvement over passive suspension method.

Reliability Assessment of Bangladesh Power System Using Recursive Algorithm

An electric utility-s main concern is to plan, design, operate and maintain its power supply to provide an acceptable level of reliability to its users. This clearly requires that standards of reliability be specified and used in all three sectors of the power system, i.e., generation, transmission and distribution. That is why reliability of a power system is always a major concern to power system planners. This paper presents the reliability analysis of Bangladesh Power System (BPS). Reliability index, loss of load probability (LOLP) of BPS is evaluated using recursive algorithm and considering no de-rated states of generators. BPS has sixty one generators and a total installed capacity of 5275 MW. The maximum demand of BPS is about 5000 MW. The relevant data of the generators and hourly load profiles are collected from the National Load Dispatch Center (NLDC) of Bangladesh and reliability index 'LOLP' is assessed for the period of last ten years.

Testing Loaded Programs Using Fault Injection Technique

Fault tolerance is critical in many of today's large computer systems. This paper focuses on improving fault tolerance through testing. Moreover, it concentrates on the memory faults: how to access the editable part of a process memory space and how this part is affected. A special Software Fault Injection Technique (SFIT) is proposed for this purpose. This is done by sequentially scanning the memory of the target process, and trying to edit maximum number of bytes inside that memory. The technique was implemented and tested on a group of programs in software packages such as jet-audio, Notepad, Microsoft Word, Microsoft Excel, and Microsoft Outlook. The results from the test sample process indicate that the size of the scanned area depends on several factors. These factors are: process size, process type, and virtual memory size of the machine under test. The results show that increasing the process size will increase the scanned memory space. They also show that input-output processes have more scanned area size than other processes. Increasing the virtual memory size will also affect the size of the scanned area but to a certain limit.

Coordination for Synchronous Cooperative Systems Based on Fuzzy Causal Relations

Synchronous cooperative systems (SCS) bring together users that are geographically distributed and connected through a network to carry out a task. Examples of SCS include Tele- Immersion and Tele-Conferences. In SCS, the coordination is the core of the system, and it has been defined as the act of managing interdependencies between activities performed to achieve a goal. Some of the main problems that SCS present deal with the management of constraints between simultaneous activities and the execution ordering of these activities. In order to resolve these problems, orderings based on Lamport-s happened-before relation have been used, namely, causal, Δ-causal, and causal-total orderings. They mainly differ in the degree of asynchronous execution allowed. One of the most important orderings is the causal order, which establishes that the events must be seen in the cause-effect order as they occur in the system. In this paper we show that for certain SCS (e.g. videoconferences, tele-immersion) where some degradation of the system is allowed, ensuring the causal order is still rigid, which can render negative affects to the system. In this paper, we illustrate how a more relaxed ordering, which we call Fuzzy Causal Order (FCO), is useful for such kind of systems by allowing a more asynchronous execution than the causal order. The benefit of the FCO is illustrated by applying it to a particular scenario of intermedia synchronization of an audio-conference system.

Evaluation of Graph-based Analysis for Forest Fire Detections

Spatial outliers in remotely sensed imageries represent observed quantities showing unusual values compared to their neighbor pixel values. There have been various methods to detect the spatial outliers based on spatial autocorrelations in statistics and data mining. These methods may be applied in detecting forest fire pixels in the MODIS imageries from NASA-s AQUA satellite. This is because the forest fire detection can be referred to as finding spatial outliers using spatial variation of brightness temperature. This point is what distinguishes our approach from the traditional fire detection methods. In this paper, we propose a graph-based forest fire detection algorithm which is based on spatial outlier detection methods, and test the proposed algorithm to evaluate its applicability. For this the ordinary scatter plot and Moran-s scatter plot were used. In order to evaluate the proposed algorithm, the results were compared with the MODIS fire product provided by the NASA MODIS Science Team, which showed the possibility of the proposed algorithm in detecting the fire pixels.