Thermo Mechanical Design and Analysis of PEM Fuel cell Plate

Fuel and oxidant gas delivery plate, or fuel cell plate, is a key component of a Proton Exchange Membrane (PEM) fuel cell. To manufacture low-cost and high performance fuel cell plates, advanced computer modeling and finite element structure analysis are used as virtual prototyping tools for the optimization of the plates at the early design stage. The present study examines thermal stress analysis of the fuel cell plates that are produced using a patented, low-cost fuel cell plate production technique based on screen-printing. Design optimization is applied to minimize the maximum stress within the plate, subject to strain constraint with both geometry and material parameters as design variables. The study reveals the characteristics of the printed plates, and provides guidelines for the structure and material design of the fuel cell plate.

Soft Real-Time Fuzzy Task Scheduling for Multiprocessor Systems

All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.

Dynamic Response of Strain Rate Dependent Glass/Epoxy Composite Beams Using Finite Difference Method

This paper deals with a numerical analysis of the transient response of composite beams with strain rate dependent mechanical properties by use of a finite difference method. The equations of motion based on Timoshenko beam theory are derived. The geometric nonlinearity effects are taken into account with von Kármán large deflection theory. The finite difference method in conjunction with Newmark average acceleration method is applied to solve the differential equations. A modified progressive damage model which accounts for strain rate effects is developed based on the material property degradation rules and modified Hashin-type failure criteria and added to the finite difference model. The components of the model are implemented into a computer code in Mathematica 6. Glass/epoxy laminated composite beams with constant and strain rate dependent mechanical properties under dynamic load are analyzed. Effects of strain rate on dynamic response of the beam for various stacking sequences, load and boundary conditions are investigated.

The New Approach to Sustainability in the Design of Urban and Architectural Interiors – Elements of Composition Revised

Today we tend to go back to the past to our root relation to nature. Therefore in search of friendly spaces there are elements of natural environment introduced as elements of spatial composition. Though reinvented through the use of the new substance such as greenery, water etc. made possible by state of the art technologies, still, in principal, they remain the same. As a result, sustainable design, based upon the recognized means of composition in addition to the relation of architecture and urbanism vs. nature introduces a new aesthetical values into architectural and urban space.

Novel Hybrid Approaches For Real Coded Genetic Algorithm to Compute the Optimal Control of a Single Stage Hybrid Manufacturing Systems

This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.

Security Analysis of Password Hardened Multimodal Biometric Fuzzy Vault

Biometric techniques are gaining importance for personal authentication and identification as compared to the traditional authentication methods. Biometric templates are vulnerable to variety of attacks due to their inherent nature. When a person-s biometric is compromised his identity is lost. In contrast to password, biometric is not revocable. Therefore, providing security to the stored biometric template is very crucial. Crypto biometric systems are authentication systems, which blends the idea of cryptography and biometrics. Fuzzy vault is a proven crypto biometric construct which is used to secure the biometric templates. However fuzzy vault suffer from certain limitations like nonrevocability, cross matching. Security of the fuzzy vault is affected by the non-uniform nature of the biometric data. Fuzzy vault when hardened with password overcomes these limitations. Password provides an additional layer of security and enhances user privacy. Retina has certain advantages over other biometric traits. Retinal scans are used in high-end security applications like access control to areas or rooms in military installations, power plants, and other high risk security areas. This work applies the idea of fuzzy vault for retinal biometric template. Multimodal biometric system performance is well compared to single modal biometric systems. The proposed multi modal biometric fuzzy vault includes combined feature points from retina and fingerprint. The combined vault is hardened with user password for achieving high level of security. The security of the combined vault is measured using min-entropy. The proposed password hardened multi biometric fuzzy vault is robust towards stored biometric template attacks.

Thermodynamic Analysis of Activated Carbon- CO2 based Adsorption Cooling Cycles

Heat powered solid sorption is a feasible alternative to electrical vapor compression refrigeration systems. In this paper, activated carbon (powder type Maxsorb and fiber type ACF-A10)- CO2 based adsorption cooling cycles are studied using the pressuretemperature- concentration (P-T-W) diagram. The specific cooling effect (SCE) and the coefficient of performance (COP) of these two cooling systems are simulated for the driving heat source temperatures ranging from 30 ºC to 90 ºC in terms of different cooling load temperatures with a cooling source temperature of 25 ºC. It is found from the present analysis that Maxsorb-CO2 couple shows higher cooling capacity and COP. The maximum COPs of Maxsorb-CO2 and ACF(A10)-CO2 based cooling systems are found to be 0.15 and 0.083, respectively. The main innovative feature of this cooling cycle is the ability to utilize low temperature waste heat or solar energy using CO2 as the refrigerant, which is one of the best alternative for applications where flammability and toxicity are not allowed.

A CUSUM Control Chart to Monitor Wafer Quality

C-control chart assumes that process nonconformities follow a Poisson distribution. In actuality, however, this Poisson distribution does not always occur. A process control for semiconductor based on a Poisson distribution always underestimates the true average amount of nonconformities and the process variance. Quality is described more accurately if a compound Poisson process is used for process control at this time. A cumulative sum (CUSUM) control chart is much better than a C control chart when a small shift will be detected. This study calculates one-sided CUSUM ARLs using a Markov chain approach to construct a CUSUM control chart with an underlying Poisson-Gamma compound distribution for the failure mechanism. Moreover, an actual data set from a wafer plant is used to demonstrate the operation of the proposed model. The results show that a CUSUM control chart realizes significantly better performance than EWMA.

Performance Evaluation of an ANC-based Hybrid Algorithm for Multi-target Wideband Active Sonar Echolocation System

This paper evaluates performances of an adaptive noise cancelling (ANC) based target detection algorithm on a set of real test data supported by the Defense Evaluation Research Agency (DERA UK) for multi-target wideband active sonar echolocation system. The hybrid algorithm proposed is a combination of an adaptive ANC neuro-fuzzy scheme in the first instance and followed by an iterative optimum target motion estimation (TME) scheme. The neuro-fuzzy scheme is based on the adaptive noise cancelling concept with the core processor of ANFIS (adaptive neuro-fuzzy inference system) to provide an effective fine tuned signal. The resultant output is then sent as an input to the optimum TME scheme composed of twogauge trimmed-mean (TM) levelization, discrete wavelet denoising (WDeN), and optimal continuous wavelet transform (CWT) for further denosing and targets identification. Its aim is to recover the contact signals in an effective and efficient manner and then determine the Doppler motion (radial range, velocity and acceleration) at very low signal-to-noise ratio (SNR). Quantitative results have shown that the hybrid algorithm have excellent performance in predicting targets- Doppler motion within various target strength with the maximum false detection of 1.5%.

Control Chart Pattern Recognition Using Wavelet Based Neural Networks

Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.

Cellulolytic Microbial Activator Influence on Decomposition of Rubber Factory Waste Composting

In this research, an aerobic composting method is studied to reuse organic waste from rubber factory waste as soil fertilizer and to study the effect of cellulolytic microbial activator (CMA) as the activator in the rubber factory waste composting. The performance of the composting process was monitored as a function of carbon and organic matter decomposition rate, temperature and moisture content. The results indicate that the rubber factory waste is best composted with water hyacinth and sludge than composted alone. In addition, the CMA is more affective when mixed with the rubber factory waste, water hyacinth and sludge since a good fertilizer is achieved. When adding CMA into the rubber factory waste composted alone, the finished product does not achieve a standard of fertilizer, especially the C/N ratio. Finally, the finished products of composting rubber factory waste and water hyacinth and sludge (both CMA and without CMA), can be an environmental friendly alternative to solve the disposal problems of rubber factory waste. Since the C/N ratio, pH, moisture content, temperature, and nutrients of the finished products are acceptable for agriculture use.

Two-Stage Compensator Designs with Partial Feedbacks

The two-stage compensator designs of linear system are investigated in the framework of the factorization approach. First, we give “full feedback" two-stage compensator design. Based on this result, various types of the two-stage compensator designs with partial feedbacks are derived.

Fuzzy Relatives of the CLARANS Algorithm With Application to Text Clustering

This paper introduces new algorithms (Fuzzy relative of the CLARANS algorithm FCLARANS and Fuzzy c Medoids based on randomized search FCMRANS) for fuzzy clustering of relational data. Unlike existing fuzzy c-medoids algorithm (FCMdd) in which the within cluster dissimilarity of each cluster is minimized in each iteration by recomputing new medoids given current memberships, FCLARANS minimizes the same objective function minimized by FCMdd by changing current medoids in such away that that the sum of the within cluster dissimilarities is minimized. Computing new medoids may be effected by noise because outliers may join the computation of medoids while the choice of medoids in FCLARANS is dictated by the location of a predominant fraction of points inside a cluster and, therefore, it is less sensitive to the presence of outliers. In FCMRANS the step of computing new medoids in FCMdd is modified to be based on randomized search. Furthermore, a new initialization procedure is developed that add randomness to the initialization procedure used with FCMdd. Both FCLARANS and FCMRANS are compared with the robust and linearized version of fuzzy c-medoids (RFCMdd). Experimental results with different samples of the Reuter-21578, Newsgroups (20NG) and generated datasets with noise show that FCLARANS is more robust than both RFCMdd and FCMRANS. Finally, both FCMRANS and FCLARANS are more efficient and their outputs are almost the same as that of RFCMdd in terms of classification rate.

The Application of Six Sigma to Integration of Computer Based Systems

This paper introduces a process for the module level integration of computer based systems. It is based on the Six Sigma Process Improvement Model, where the goal of the process is to improve the overall quality of the system under development. We also present a conceptual framework that shows how this process can be implemented as an integration solution. Finally, we provide a partial implementation of key components in the conceptual framework.

Solving Machine Loading Problem in Flexible Manufacturing Systems Using Particle Swarm Optimization

In this paper, a particle swarm optimization (PSO) algorithm is proposed to solve machine loading problem in flexible manufacturing system (FMS), with bicriterion objectives of minimizing system unbalance and maximizing system throughput in the occurrence of technological constraints such as available machining time and tool slots. A mathematical model is used to select machines, assign operations and the required tools. The performance of the PSO is tested by using 10 sample dataset and the results are compared with the heuristics reported in the literature. The results support that the proposed PSO is comparable with the algorithms reported in the literature.

Direct Measurements of Wind Data over 100 Meters above the Ground in the Site of Lendinara, Italy

The wind resource in the Italian site of Lendinara (RO) is analyzed through a systematic anemometric campaign performed on the top of the bell tower, at an altitude of over 100 m above the ground. Both the average wind speed and the Weibull distribution are computed. The resulting average wind velocity is in accordance with the numerical predictions of the Italian Wind Atlas, confirming the accuracy of the extrapolation of wind data adopted for the evaluation of wind potential at higher altitudes with respect to the commonly placed measurement stations.

Analysis of a Mathematical Model for Dengue Disease in Pregnant Cases

Dengue fever is an important human arboviral disease. Outbreaks are now reported quite often from many parts of the world. The number of cases involving pregnant women and infant cases are increasing every year. The illness is often severe and complications may occur. Deaths often occur because of the difficulties in early diagnosis and in the improper management of the diseases. Dengue antibodies from pregnant women are passed on to infants and this protects the infants from dengue infections. Antibodies from the mother are transferred to the fetus when it is still in the womb. In this study, we formulate a mathematical model to describe the transmission of this disease in pregnant women. The model is formulated by dividing the human population into pregnant women and non-pregnant human (men and non-pregnant women). Each class is subdivided into susceptible (S), infectious (I) and recovered (R) subclasses. We apply standard dynamical analysis to our model. Conditions for the local stability of the equilibrium points are given. The numerical simulations are shown. The bifurcation diagrams of our model are discussed. The control of this disease in pregnant women is discussed in terms of the threshold conditions.

Performance of Bio-Composite Carbonized Materials in Probiotic Applications

A new composite sorbent based on carbonized rice husk (CRH) and immobilized on it living cells and inactivated cultural liquid containing antimicrobials metabolites of Bacillus subtilis CK-245 is developed. The sorption and antimicrobic activity of CRH concerning five species of Enterobacteriaceae is studied. Prospects of use of developed sorbent in medicine and veterinary science is shown.

Versatile Dual-Mode Class-AB Four-Quadrant Analog Multiplier

Versatile dual-mode class-AB CMOS four-quadrant analog multiplier circuit is presented. The dual translinear loops and current mirrors are the basic building blocks in realization scheme. This technique provides; wide dynamic range, wide-bandwidth response and low power consumption. The major advantages of this approach are; its has single ended inputs; since its input is dual translinear loop operate in class-AB mode which make this multiplier configuration interesting for low-power applications; current multiplying, voltage multiplying, or current and voltage multiplying can be obtainable with balanced input. The simulation results of versatile analog multiplier demonstrate a linearity error of 1.2 %, a -3dB bandwidth of about 19MHz, a maximum power consumption of 0.46mW, and temperature compensated. Operation of versatile analog multiplier was also confirmed through an experiment using CMOS transistor array.

Towards Medical Device Maintenance Workflow Monitoring

Concerning the inpatient care the present situation is characterized by intense charges of medical technology into the clinical daily routine and an ever stronger integration of special techniques into the clinical workflow. Medical technology is by now an integral part of health care according to consisting general accepted standards. Purchase and operation thereby represent an important economic position and both are subject of everyday optimisation attempts. For this purpose by now exists a huge number of tools which conduce more likely to a complexness of the problem by a comprehensive implementation. In this paper the advantages of an integrative information-workflow on the life-cycle-management in the region of medical technology are shown.