Performance of a Power Generator System Using Crude Plant Oil Blend with Diesel Fuel

Under the variation of crude oil price and the impact of greenhouse effect, it is urgent to find a potential alternative fuel. Among these alternative fuels, non edible plant oils are the most potential ones, because they don-t have the problem of food and cropland competitions. Among the non-edible plant oils, Jatropha oil is the most potential one. Jatropha oil is non-eatable oil and has good oil quality and low temperature performance. It has potential to become one of the most competitive biomass crude oils. The crude plant oil will be blended with diesel fuel to be tested in a power generator. The international collaboration between Taiwan and Indonesia on the production of Jatropha in Indonesia will also be presented in this study.

Analyzing of Public Transport Trip Generation in Developing Countries; A Case Study in Yogyakarta, Indonesia

Yogyakarta, as the capital city of Yogyakarta Province, has important roles in various sectors that require good provision of public transportation system. Ideally, a good transportation system should be able to accommodate the amount of travel demand. This research attempts to develop a trip generation model to predict the number of public transport passenger in Yogyakarta city. The model is built by using multiple linear regression analysis, which establishes relationship between trip number and socioeconomic attributes. The data consist of primary and secondary data. Primary data was collected by conducting household surveys which randomly selected. The resulted model is further applied to evaluate the existing TransJogja, a new Bus Rapid Transit system serves Yogyakarta and surrounding cities, shelters.

The Anti-Noise and Anti-Wear Systems for Railways

In recent years there has been a continuous increase of axle loads, tonnage, train speed and train length which has increased both the productivity in the rail sector and the risk of rail breaks and derailments. On the other hand, the environmental requirements (e.g. noise reduction) for railway operations will become tighter in the future. In our research we developed a new composite material which does not change braking properties, is capable of taking extremely high pressure loads, reduces noise and is environmentally friendly. Part of our research was also the development of technology which will be able to apply this material to the rail. The result of our research was the system which reduces the wear out significantly and almost completely eliminates the squealing noise at the same time, and by using only one special material.

A Preliminary X-Ray Study on Human-Hair Microstructures for a Health-State Indicator

We present a preliminary x-ray study on human-hair microstructures for a health-state indicator, in particular a cancer case. As an uncomplicated and low-cost method of x-ray technique, the human-hair microstructure was analyzed by wide-angle x-ray diffractions (XRD) and small-angle x-ray scattering (SAXS). The XRD measurements exhibited the simply reflections at the d-spacing of 28 Å, 9.4 Å and 4.4 Å representing to the periodic distance of the protein matrix of the human-hair macrofibrous and the diameter and the repeated spacing of the polypeptide alpha helixes of the photofibrils of the human-hair microfibrous, respectively. When compared to the normal cases, the unhealthy cases including to the breast- and ovarian-cancer cases obtained higher normalized ratios of the x-ray diffracting peaks of 9.4 Å and 4.4 Å. This likely resulted from the varied distributions of microstructures by a molecular alteration. As an elemental analysis by x-ray fluorescence (XRF), the normalized quantitative ratios of zinc(Zn)/calcium(Ca) and iron(Fe)/calcium(Ca) were determined. Analogously, both Zn/Ca and Fe/Ca ratios of the unhealthy cases were obtained higher than both of the normal cases were. Combining the structural analysis by XRD measurements and the elemental analysis by XRF measurements exhibited that the modified fibrous microstructures of hair samples were in relation to their altered elemental compositions. Therefore, these microstructural and elemental analyses of hair samples will be benefit to associate with a diagnosis of cancer and genetic diseases. This functional method would lower a risk of such diseases by the early diagnosis. However, the high-intensity x-ray source, the highresolution x-ray detector, and more hair samples are necessarily desired to develop this x-ray technique and the efficiency would be enhanced by including the skin and fingernail samples with the human-hair analysis.

Panel Zone Rigidity Effects on Special Steel Moment-Resisting Frames According to the Performance Based Design

The unanticipated destruct of more of the steel moment frames in Northridge earthquake, altered class of regard to the beamto- column connections in moment frames. Panel zone is one the significant part of joints which, it-s stiffness and rigidity has an important effect on the behavior and ductility of the frame. Specifically that behavior of panel zone has a very significant effect on the special moment frames. In this paper , meanwhile the relations for modeling of panel zone in frames are expressed , special moment frames with different spans and stories were studied in the way of performance-based design. The frames designed in according with Iranian steel building code. The effect of panel zone is also considered and in the case of non-existence of performance level, by changing in intimacies and parameter of panel zone, performance level is considered.

A Fuzzy Predictive Filter for Sinusoidal Signals with Time-Varying Frequencies

Prediction of sinusoidal signals with time-varying frequencies has been an important research topic in power electronics systems. To solve this problem, we propose a new fuzzy predictive filtering scheme, which is based on a Finite Impulse Response (FIR) filter bank. Fuzzy logic is introduced here to provide appropriate interpolation of individual filter outputs. Therefore, instead of regular 'hard' switching, our method has the advantageous 'soft' switching among different filters. Simulation comparisons between the fuzzy predictive filtering and conventional filter bank-based approach are made to demonstrate that the new scheme can achieve an enhanced prediction performance for slowly changing sinusoidal input signals.

Comparison of the Existing Methods in Determination of the Characteristic Polynomial

This paper presents comparison among methods of determination of the characteristic polynomial coefficients. First, the resultant systems from the methods are compared based on frequency criteria such as the closed loop bandwidth, gain and phase margins. Then the step responses of the resultant systems are compared on the basis of the transient behavior criteria including overshoot, rise time, settling time and error (via IAE, ITAE, ISE and ITSE integral indices). Also relative stability of the systems is compared together. Finally the best choices in regards to the above diverse criteria are presented.

Novel SNC-NN-MRAS Based Speed Estimator for Sensor-Less Vector Controlled IM Drives

Rotor Flux based Model Reference Adaptive System (RF-MRAS) is the most popularly used conventional speed estimation scheme for sensor-less IM drives. In this scheme, the voltage model equations are used for the reference model. This encounters major drawbacks at low frequencies/speed which leads to the poor performance of RF-MRAS. Replacing the reference model using Neural Network (NN) based flux estimator provides an alternate solution and addresses such drawbacks. This paper identifies an NN based flux estimator using Single Neuron Cascaded (SNC) Architecture. The proposed SNC-NN model replaces the conventional voltage model in RF-MRAS to form a novel MRAS scheme named as SNC-NN-MRAS. Through simulation the proposed SNC-NN-MRAS is shown to be promising in terms of all major issues and robustness to parameter variation. The suitability of the proposed SNC-NN-MRAS based speed estimator and its advantages over RF-MRAS for sensor-less induction motor drives is comprehensively presented through extensive simulations.

The System Identification and PID Lead-lag Control for Two Poles Unstable SOPDT Process by Improved Relay Method

This paper describes identification of the two poles unstable SOPDT process, especially with large time delay. A new modified relay feedback identification method for two poles unstable SOPDT process is proposed. Furthermore, for the two poles unstable SOPDT process, an additional Derivative controller is incorporated parallel with relay to relax the constraint on the ratio of delay to the unstable time constant, so that the exact model parameters of unstable processes can be identified. To cope with measurement noise in practice, a low pass filter is suggested to get denoised output signal toimprove the exactness of model parameter of unstable process. PID Lead-lag tuning formulas are derived for two poles unstable (SOPDT) processes based on IMC principle. Simulation example illustrates the effectiveness and the simplicity of the proposed identification and control method.

Confidence Intervals for the Difference of Two Normal Population Variances

Motivated by the recent work of Herbert, Hayen, Macaskill and Walter [Interval estimation for the difference of two independent variances. Communications in Statistics, Simulation and Computation, 40: 744-758, 2011.], we investigate, in this paper, new confidence intervals for the difference between two normal population variances based on the generalized confidence interval of Weerahandi [Generalized Confidence Intervals. Journal of the American Statistical Association, 88(423): 899-905, 1993.] and the closed form method of variance estimation of Zou, Huo and Taleban [Simple confidence intervals for lognormal means and their differences with environmental applications. Environmetrics 20: 172-180, 2009]. Monte Carlo simulation results indicate that our proposed confidence intervals give a better coverage probability than that of the existing confidence interval. Also two new confidence intervals perform similarly based on their coverage probabilities and their average length widths.

Wavelet-Based Despeckling of Synthetic Aperture Radar Images Using Adaptive and Mean Filters

In this paper we introduced new wavelet based algorithm for speckle reduction of synthetic aperture radar images, which uses combination of undecimated wavelet transformation, wiener filter (which is an adaptive filter) and mean filter. Further more instead of using existing thresholding techniques such as sure shrinkage, Bayesian shrinkage, universal thresholding, normal thresholding, visu thresholding, soft and hard thresholding, we use brute force thresholding, which iteratively run the whole algorithm for each possible candidate value of threshold and saves each result in array and finally selects the value for threshold that gives best possible results. That is why it is slow as compared to existing thresholding techniques but gives best results under the given algorithm for speckle reduction.

A New Algorithm for Enhanced Robustness of Copyright Mark

This paper discusses a new heavy tailed distribution based data hiding into discrete cosine transform (DCT) coefficients of image, which provides statistical security as well as robustness against steganalysis attacks. Unlike other data hiding algorithms, the proposed technique does not introduce much effect in the stegoimage-s DCT coefficient probability plots, thus making the presence of hidden data statistically undetectable. In addition the proposed method does not compromise on hiding capacity. When compared to the generic block DCT based data-hiding scheme, our method found more robust against a variety of image manipulating attacks such as filtering, blurring, JPEG compression etc.

Urban Land Cover Change of Olomouc City Using LANDSAT Images

This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.

The Potential of Natural Waste (Corn Husk) for Production of Environmental Friendly Biodegradable Film for Seedling

The use of plastic materials in agriculture causes serious hazards to the environment. The introduction of biodegradable materials, which can be disposed directly into the soil can be one possible solution to this problem. In the present research results of experimental tests carried out on biodegradable film fabricated from natural waste (corn husk) are presented. The film was characterized by Fourier transform infrared spectroscopy (FTIR), differential scanning calorimeter (DSC), thermal gravimetric analysis (TGA) and atomic force microscope (AFM) observation. The film is shown to be readily degraded within 7-9 months under controlled soil conditions, indicating a high biodegradability rate. The film fabricated was use to produce biodegradable pot (BioPot) for seedlings plantation. The introduction and the expanding use of biodegradable materials represent a really promising alternative for enhancing sustainable and environmentally friendly agricultural activities.

Broadband PowerLine Communications: Performance Analysis

Power line channel is proposed as an alternative for broadband data transmission especially in developing countries like Tanzania [1]. However the channel is affected by stochastic attenuation and deep notches which can lead to the limitation of channel capacity and achievable data rate. Various studies have characterized the channel without giving exactly the maximum performance and limitation in data transfer rate may be this is due to complexity of channel modeling being used. In this paper the channel performance of medium voltage, low voltage and indoor power line channel is presented. In the investigations orthogonal frequency division multiplexing (OFDM) with phase shift keying (PSK) as carrier modulation schemes is considered, for indoor, medium and low voltage channels with typical ten branches and also Golay coding is applied for medium voltage channel. From channels, frequency response deep notches are observed in various frequencies which can lead to reduce the achievable data rate. However, is observed that data rate up to 240Mbps is realized for a signal to noise ratio of about 50dB for indoor and low voltage channels, however for medium voltage a typical link with ten branches is affected by strong multipath and coding is required for feasible broadband data transfer.

Face Localization Using Illumination-dependent Face Model for Visual Speech Recognition

A robust still image face localization algorithm capable of operating in an unconstrained visual environment is proposed. First, construction of a robust skin classifier within a shifted HSV color space is described. Then various filtering operations are performed to better isolate face candidates and mitigate the effect of substantial non-skin regions. Finally, a novel Bhattacharyya-based face detection algorithm is used to compare candidate regions of interest with a unique illumination-dependent face model probability distribution function approximation. Experimental results show a 90% face detection success rate despite the demands of the visually noisy environment.

Particle Swarm Optimization for Design of Water Distribution Systems

Particle swarm optimization (PSO) technique is applied to design the water distribution pipeline network. A simulation-optimization model is formulated with the objective of minimizing cost and is applied to a benchmark water distribution system optimization problem. The benchmark problem taken for the application of PSO technique to optimize the pipe size of the water distribution network is New York City water supply system problem. The results from the analysis infer that PSO is a potential alternative optimization technique when compared to other heuristic techniques for optimal sizing of water distribution systems.

Study on Nitrite Accumulation Characteristics and Nitrifying Population Dynamics at Different Growth Environments

Novel nitrogen removal technologies via nitrite pathway attract increasing interest in recent years. In this study, batch experiments were performed to investigate nitrite accumulation characteristics and shifts in nitrifying community structure at different growth environments including ammonia concentration, pH and alkalinity. It was found that nitrite accumulation ratios were maintained at around 95% at studied conditions, and the optimum pH and Alk/N (ratio between alkalinity and nitrogen) for ammonium oxidization were 8.5 and 8.33, respectively. Fluorescence in situ hybridization analysis of nitrifying bacteria showed that high free ammonia (from influent ammonium or caused by high pH) significantly altered the structure of nitrifying community, leading to abundance of ammonia-oxidizing bacteria (AOB), especially Nitrososmonas, and inhibition of nitrite-oxidizing bacteria (NOB). The results suggest that free ammonia plays more important role than other studied conditions on nitrite accumulation.

Novel Methods for Desulfurization of Fuel Oils

Because of the requirement for low sulfur content of fuel oils, it is necessary to develop alternative methods for desulfurization of heavy fuel oil. Due to the disadvantages of HDS technologies such as costs, safety and green environment, new methods have been developed. Among these methods is ultrasoundassisted oxidative desulfurization. Using ultrasound-assisted oxidative desulfurization, compounds such as benzothiophene and dibenzothiophene can be oxidized. As an alternative method is sulfur elimination of heavy fuel oil by using of activated carbon in a packed column in batch condition. The removal of sulfur compounds in this case to reach about 99%. The most important property of activated carbon is ability of it for adsorption, which is due to high surface area and pore volume of it.

Layout Based Spam Filtering

Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel approach to filtering based solely on layout, whose goal is not only to correctly identify spam, but also warn about major emerging threats. We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types.