The Cost Structure of Intermodal Transportation: The Chilean Case

This study defines a methodology to compute unitary costs for freight transportation modes. The main objective was to gather relevant costs data to support the formulation and evaluation of railway, road, pipelines and port projects. This article will concentrate on the following steps: Compilation and analysis of relevant modal cost studies, Methodological adjustments to make cost figures comparable between studies, Definition of typology and scope of transportation modes, Analysis and validation of cost values for relevant freight transportation modes in Chile. In order to define the comparison methodology for the costs between the different transportation modes, it was necessary to consider that the relevant cost depends on who performs the comparison. Thus, for the transportation user (e.g. exporter) the pertinent costs are the mode tariffs, whereas from the operators perspective (e.g. rail manager), the pertinent costs are the operating costs of each mode.

The Estimation of Semi Elliptical Surface Cracks Advancement via Fuzzy Logic

This paper presented the results of an experimental investigation into the axial fatigue behavior of a 5086 aluminum alloy which have several notch-aspect ratios a0/c0 and notch thickness ratio a/t with semi-elliptical surface cracks. Tests were conducted in la b air for stress levels of 50 % of their yield strength. Experiments were carried out for various notch to thickness ratios. Crack growth rates of test specimens both in surface and depth directions were determined by using die penetration method. Fuzzy Logic method was used to predict the deep direction crack growth because the dept of the crack is considerably difficult to measure.

Aerobic Treatment of Oily Wastewater: Effect of Aeration and Sludge Concentration to Pollutant Reduction and PHB Accumulation

This study is aimed to investigate feasibility of the aerobic biological process to treat oily wastewater from palm oil food industry. Effect of aeration and sludge concentrations are studied. Raw sludge and raw wastewater was mixed and acclimatized for five days in a stirred tank reactor. The aeration rate (no aeration, low; 1.5L/min and high rate; 2L/min) and sludge concentration (3675, 7350, and 11025mg/L of VSS) were varied. Responses of process were pH, COD, oil and grease, VSS, and PHB content. It was found that the treatment can remove 85.1 to 97.1 % of COD and remove 12.9 to 54.8% of oil & grease. The PHB yield was found to be within 0.15% to 2.4% as PHB/VSS ratio and 0.01% to 0.12% as PHB/COD removed. The higher aeration results a high COD removal and oil & grease removal, while experiment without aeration gives better PHB yield. Higher sludge concentrations (11025mg/L VSS) give higher removal of oil & grease while moderate sludge concentration (7350mg/L VSS) give better result in COD removal. Higher PHB yield is obtained in low sludge concentration (3675mg/L).

Meta-reasoning for Multi-agent Communication of Semantic Web Information

Meta-reasoning is essential for multi-agent communication. In this paper we propose a framework of multi-agent communication in which agents employ meta-reasoning to reason with agent and ontology locations in order to communicate semantic information with other agents on the semantic web and also reason with multiple distributed ontologies. We shall argue that multi-agent communication of Semantic Web information cannot be realized without the need to reason with agent and ontology locations. This is because for an agent to be able to communicate with another agent, it must know where and how to send a message to that agent. Similarly, for an agent to be able to reason with an external semantic web ontology, it must know where and how to access to that ontology. The agent framework and its communication mechanism are formulated entirely in meta-logic.

The Kinetic of Biodegradation Lignin in Water Hyacinth (Eichhornia Crassipes) by Phanerochaete Chrysosporium using Solid State Fermentation (SSF) Method for Bioethanol Production, Indonesia

Lignocellulosic materials are considered the most abundant renewable resource available for the Bioethanol Production. Water Hyacinth is one of potential raw material of the world-s worst aquatic plant as a feedstock to produce Bioethanol. The purposed this research is obtain reduced of matter for biodegradation lignin in Biological pretreatment with White Rot Fungi eg. Phanerochaete Chrysosporium using Solid state Fermentation methods. Phanerochaete Chrysosporium is known to have the best ability to degraded lignin, but simultaneously it can also degraded cellulose and hemicelulose. During 8 weeks incubation, water hyacinth occurred loss of weight reached 34,67%, while loss of lignin reached 67,21%, loss of cellulose reached 11,01% and loss of hemicellulose reached 36,56%. The kinetic of losses lignin using regression linear plot, the results is obtained constant rate (k) of reduction lignin is -0.1053 and the equation of reduction of lignin is y = wo - 0, 1.53 x

Effect of Different Fertilization Methods on Soil Biological Indexes

Fertilization plays an important role in crop growth and soil improvement. This study was conducted to determine the best fertilization system for wheat production. Experiments were arranged in a complete block design with three replications in two years. Main plots consisted of six methods of fertilization including (N1): farmyard manure; (N2): compost; (N3): chemical fertilizers; (N4): farmyard manure + compost; (N5): farmyard manure + compost + chemical fertilizers and (N6): control were arranged in sub plots. The addition of compost or farm yard manure significantly increased the soil microbial biomass carbon in comparison to the chemical fertilizer. The dehydrogenase, phosphatase and urease activities in the N3 treatment were significantly lower than in the farm yard manure and compost treatments.

An Energy Efficient Algorithm for Distributed Mutual Exclusion in Mobile Ad-hoc Networks

This paper reports a distributed mutual exclusion algorithm for mobile Ad-hoc networks. The network is clustered hierarchically. The proposed algorithm considers the clustered network as a logical tree and develops a token passing scheme to get the mutual exclusion. The performance analysis and simulation results show that its message requirement is optimal, and thus the algorithm is energy efficient.

Prediction of Dissolved Oxygen in Rivers Using a Wang-Mendel Method – Case Study of Au Sable River

Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.

A New Ridge Orientation based Method of Computation for Feature Extraction from Fingerprint Images

An important step in studying the statistics of fingerprint minutia features is to reliably extract minutia features from the fingerprint images. A new reliable method of computation for minutiae feature extraction from fingerprint images is presented. A fingerprint image is treated as a textured image. An orientation flow field of the ridges is computed for the fingerprint image. To accurately locate ridges, a new ridge orientation based computation method is proposed. After ridge segmentation a new method of computation is proposed for smoothing the ridges. The ridge skeleton image is obtained and then smoothed using morphological operators to detect the features. A post processing stage eliminates a large number of false features from the detected set of minutiae features. The detected features are observed to be reliable and accurate.

Biosynthesis and In vitro Studies of Silver Bionanoparticles Synthesized from Aspergillusspecies and its Antimicrobial Activity against Multi Drug Resistant Clinical Isolates

Antimicrobial resistant is becoming a major factor in virtually all hospital acquired infection may soon untreatable is a serious public health problem. These concerns have led to major research effort to discover alternative strategies for the treatment of bacterial infection. Nanobiotehnology is an upcoming and fast developing field with potential application for human welfare. An important area of nanotechnology for development of reliable and environmental friendly process for synthesis of nanoscale particles through biological systems In the present studies are reported on the use of fungal strain Aspergillus species for the extracellular synthesis of bionanoparticles from 1 mM silver nitrate (AgNO3) solution. The report would be focused on the synthesis of metallic bionanoparticles of silver using a reduction of aqueous Ag+ ion with the culture supernatants of Microorganisms. The bio-reduction of the Ag+ ions in the solution would be monitored in the aqueous component and the spectrum of the solution would measure through UV-visible spectrophotometer The bionanoscale particles were further characterized by Atomic Force Microscopy (AFM), Fourier Transform Infrared Spectroscopy (FTIR) and Thin layer chromatography. The synthesized bionanoscale particle showed a maximum absorption at 385 nm in the visible region. Atomic Force Microscopy investigation of silver bionanoparticles identified that they ranged in the size of 250 nm - 680 nm; the work analyzed the antimicrobial efficacy of the silver bionanoparticles against various multi drug resistant clinical isolates. The present Study would be emphasizing on the applicability to synthesize the metallic nanostructures and to understand the biochemical and molecular mechanism of nanoparticles formation by the cell filtrate in order to achieve better control over size and polydispersity of the nanoparticles. This would help to develop nanomedicine against various multi drug resistant human pathogens.

Automatic 3D Reconstruction of Coronary Artery Centerlines from Monoplane X-ray Angiogram Images

We present a new method for the fully automatic 3D reconstruction of the coronary artery centerlines, using two X-ray angiogram projection images from a single rotating monoplane acquisition system. During the first stage, the input images are smoothed using curve evolution techniques. Next, a simple yet efficient multiscale method, based on the information of the Hessian matrix, for the enhancement of the vascular structure is introduced. Hysteresis thresholding using different image quantiles, is used to threshold the arteries. This stage is followed by a thinning procedure to extract the centerlines. The resulting skeleton image is then pruned using morphological and pattern recognition techniques to remove non-vessel like structures. Finally, edge-based stereo correspondence is solved using a parallel evolutionary optimization method based on f symbiosis. The detected 2D centerlines combined with disparity map information allow the reconstruction of the 3D vessel centerlines. The proposed method has been evaluated on patient data sets for evaluation purposes.

Human Verification in a Video Surveillance System Using Statistical Features

A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.

Challenges to Technological Advancement in Economically Weak Countries: An Assessment of the Nigerian Educational Situation

Nigeria is considered as one of the many countries in sub-Saharan Africa with a weak economy and gross deficiencies in technology and engineering. Available data from international monitoring and regulatory organizations show that technology is pivotal to determining the economic strengths of nations all over the world. Education is critical to technology acquisition, development, dissemination and adaptation. Thus, this paper seeks to critically assess and discuss issues and challenges facing technological advancement in Nigeria, particularly in the education sector, and also proffers solutions to resuscitate the Nigerian education system towards achieving national technological and economic sustainability such that Nigeria can compete favourably with other technologicallydriven economies of the world in the not-too-distant future.

Validation of Automation Systems using Temporal Logic Model Checking and Groebner Bases

Validation of an automation system is an important issue. The goal is to check if the system under investigation, modeled by a Petri net, never enters the undesired states. Usually, tools dedicated to Petri nets such as DESIGN/CPN are used to make reachability analysis. The biggest problem with this approach is that it is impossible to generate the full occurence graph of the system because it is too large. In this paper, we show how computational methods such as temporal logic model checking and Groebner bases can be used to verify the correctness of the design of an automation system. We report our experimental results with two automation systems: the Automated Guided Vehicle (AGV) system and the traffic light system. Validation of these two systems ranged from 10 to 30 seconds on a PC depending on the optimizing parameters.

Distinguishing Innocent Murmurs from Murmurs caused by Aortic Stenosis by Recurrence Quantification Analysis

It is sometimes difficult to differentiate between innocent murmurs and pathological murmurs during auscultation. In these difficult cases, an intelligent stethoscope with decision support abilities would be of great value. In this study, using a dog model, phonocardiographic recordings were obtained from 27 boxer dogs with various degrees of aortic stenosis (AS) severity. As a reference for severity assessment, continuous wave Doppler was used. The data were analyzed with recurrence quantification analysis (RQA) with the aim to find features able to distinguish innocent murmurs from murmurs caused by AS. Four out of eight investigated RQA features showed significant differences between innocent murmurs and pathological murmurs. Using a plain linear discriminant analysis classifier, the best pair of features (recurrence rate and entropy) resulted in a sensitivity of 90% and a specificity of 88%. In conclusion, RQA provide valid features which can be used for differentiation between innocent murmurs and murmurs caused by AS.

Synthesis of Logic Circuits Using Fractional-Order Dynamic Fitness Functions

This paper analyses the performance of a genetic algorithm using a new concept, namely a fractional-order dynamic fitness function, for the synthesis of combinational logic circuits. The experiments reveal superior results in terms of speed and convergence to achieve a solution.

Spent Caustic Bioregeneration by using Thiobacillus denitrificans Bacteria

Spent Sulfidic Caustic was biologically treated and regenerated for reusing by Thiobacillus denitrificans bacteria, sulfide content oxidized and RSNa reduced dramatically.PH in this test was 11.8 and no neutralization has been done on spent caustic, so spent caustic as the most difficult of industrial wastes to dispose could be regenerate and reuse instead of disposing to sea or deep wells

Temporal Analysis of Magnetic Nerve Stimulation–Towards Enhanced Systems via Virtualisation

The triumph of inductive neuro-stimulation since its rediscovery in the 1980s has been quite spectacular. In lots of branches ranging from clinical applications to basic research this system is absolutely indispensable. Nevertheless, the basic knowledge about the processes underlying the stimulation effect is still very rough and rarely refined in a quantitative way. This seems to be not only an inexcusable blank spot in biophysics and for stimulation prediction, but also a fundamental hindrance for technological progress. The already very sophisticated devices have reached a stage where further optimization requires better strategies than provided by simple linear membrane models of integrate-and-fire style. Addressing this problem for the first time, we suggest in the following text a way for virtual quantitative analysis of a stimulation system. Concomitantly, this ansatz seems to provide a route towards a better understanding by using nonlinear signal processing and taking the nerve as a filter that is adapted for neuronal magnetic stimulation. The model is compact and easy to adjust. The whole setup behaved very robustly during all performed tests. Exemplarily a recent innovative stimulator design known as cTMS is analyzed and dimensioned with this approach in the following. The results show hitherto unforeseen potentials.

In Search of Robustness and Efficiency via l1− and l2− Regularized Optimization for Physiological Motion Compensation

Compensating physiological motion in the context of minimally invasive cardiac surgery has become an attractive issue since it outperforms traditional cardiac procedures offering remarkable benefits. Owing to space restrictions, computer vision techniques have proven to be the most practical and suitable solution. However, the lack of robustness and efficiency of existing methods make physiological motion compensation an open and challenging problem. This work focusses on increasing robustness and efficiency via exploration of the classes of 1−and 2−regularized optimization, emphasizing the use of explicit regularization. Both approaches are based on natural features of the heart using intensity information. Results pointed out the 1−regularized optimization class as the best since it offered the shortest computational cost, the smallest average error and it proved to work even under complex deformations.

Neuroblasts Micropatterning on Nanostructural Modified Chitosan Membranes

The study describes chitosan membrane platform modified with nanostructure pattern which using nanotechnology to fabricate. The cell-substrate interaction between neuro-2a neuroblasts cell lines and chitosan membrane (flat, nanostructure and nanostructure pattern types) was investigated. The adhered morphology of neuro-2a cells depends on the topography of chitosan surface. We have found that neuro-2a showed different morphogenesis when cells adhered on flat and nanostructure chitosan membrane. The cell projected area of neuro-2a on flat chitosan membrane is larger than on nanostructure chitosan membrane. In addition, neuro-2a cells preferred to adhere on flat chitosan surface region than on nanostructure chitosan membrane to immobilize and differentiation. The experiment suggests surface topography can be used as a critical mechanism to isolate group of neuro-2a to a particular rectangle area on chitosan membrane. Our finding will provide a platform to take patch clamp to record electrophysiological behavior about neurons in vitro in the future.