Experimental Investigation on the Effect of CO2 and WAG Injection on Permeability Reduction Induced by Asphaltene Precipitation in Light Oil

Permeability reduction induced by asphaltene precipitation during gas injection is one of the serious problems in the oil industry. This problem can lead to formation damage and decrease the oil production rate. In this work, Malaysian light oil sample has been used to investigate the effect CO2 injection and Water Alternating Gas (WAG) injection on permeability reduction. In this work, dynamic core flooding experiments were conducted to study the effect of CO2 and WAG injection on the amount of asphaltene precipitated. Core properties after displacement were inspected for any permeability reduction to study the effect of asphaltene precipitation on rock properties. The results showed that WAG injection gave less asphaltene precipitation and formation damage compared to CO2 injection. The study suggested that WAG injection can be one of the important factors of managing asphaltene precipitation.

Treatment of Biowaste (Generated in Biodiesel Process) - A New Strategy for Green Environment and Horticulture Crop

Recent research on seeds of bio-diesel plants like Jatropha curcas, constituting 40-50% bio-crude oil indicates its potential as one of the most promising alternatives to conventional sources of energy. Also, limited studies on utilization of de-oiled cake have revealed that Jatropha bio-waste has good potential to be used as organic fertilizers produced via aerobic and anaerobic treatment. However, their commercial exploitation has not yet been possible. The present study aims at developing appropriate bio-processes and formulations utilizing Jatropha seed cake as organic fertilizer, for improving the growth of Polianthes tuberose L. (Tuberose). Pot experiments were carried out by growing tuberose plants on soil treated with composted formulations of Jatropha de-oiled cake, Farm Yard Manure (FYM) and inorganic fertilizers were also blended in soil. The treatment was carried out through soil amendment as well as foliar spray. The growth and morphological parameters were monitored for entire crop cycle. The growth Length and number of leaves, spike length, rachis length, number of bulb per plant and earliness of sprouting of bulb and yield enhancement were comparable to that achieved under inorganic fertilizer. Furthermore, performance of inorganic fertilizer also showed an improvement when blended with composted bio-waste. These findings would open new avenues for Jatropha based bio-wastes to be composted and used as organic fertilizers for commercial floriculture.

Concept Indexing using Ontology and Supervised Machine Learning

Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.

Highly Efficient White Light-emitting Diodes Based on Layered Quantum Dot-Phosphor Nanocomposites as Converting Materials

This paper reports on the enhanced photoluminescence (PL) of nanocomposites through the layered structuring of phosphor and quantum dot (QD). Green phosphor of Sr2SiO4:Eu, red QDs of CdSe/CdS/CdZnS/ZnS core-multishell, and thermo-curable resin were used for this study. Two kinds of composite (layered and mixed) were prepared, and the schemes for optical energy transfer between QD and phosphor were suggested and investigated based on PL decay characteristics. It was found that the layered structure is more effective than the mixed one in the respects of PL intensity, PL decay and thermal loss. When this layered nanocomposite (QDs on phosphor) is used to make white light emitting diode (LED), the brightness is increased by 37 %, and the color rendering index (CRI) value is raised to 88.4 compared to the mixed case of 80.4.

Elections, Checks and Balances, and Government Expenditures: Empirical Evidence for Japan, South Korea, and Taiwan

Previous studies on political budget cycles (PBCs) implicitly assume the executive has full discretion power over fiscal policy, neglecting the role of checks and balances of the legislature. This paper goes beyond traditional PBCs models and sheds light on the case study of Japan, South Korea, and Taiwan over the 1988-2007 periods. Based on the results, we find no evidence of electoral impacts on the public expenditures in South Korean and Taiwan's congressional elections. We also noted that PBCs are found on Taiwan-s government expenditures during our sample periods. Furthermore, the results also show that Japan-s legislature has a significant checks and balances on government-s expenditures. However, empirical results show that the legislature veto player in Taiwan neither has effect on the reduction of public expenditures, nor has the moderating effect over Taiwan-s political budget cycles, albeit that they are statistically insignificant.We suggest that the existence of PBCs in Taiwan is due to a weaker systemof checks and balances. Our conjecture is that Taiwan either has no legislative veto player or has observed low compliance to the law during the time period examined in our study.

A Fast Neural Algorithm for Serial Code Detection in a Stream of Sequential Data

In recent years, fast neural networks for object/face detection have been introduced based on cross correlation in the frequency domain between the input matrix and the hidden weights of neural networks. In our previous papers [3,4], fast neural networks for certain code detection was introduced. It was proved in [10] that for fast neural networks to give the same correct results as conventional neural networks, both the weights of neural networks and the input matrix must be symmetric. This condition made those fast neural networks slower than conventional neural networks. Another symmetric form for the input matrix was introduced in [1-9] to speed up the operation of these fast neural networks. Here, corrections for the cross correlation equations (given in [13,15,16]) to compensate for the symmetry condition are presented. After these corrections, it is proved mathematically that the number of computation steps required for fast neural networks is less than that needed by classical neural networks. Furthermore, there is no need for converting the input data into symmetric form. Moreover, such new idea is applied to increase the speed of neural networks in case of processing complex values. Simulation results after these corrections using MATLAB confirm the theoretical computations.

Thermodynamic Study of Hot Potassium Carbonate Solution Using Aspen Plus

This paper presents a study on the thermodynamics and transport properties of hot potassium carbonate aqueous system (HPC) using electrolyte non-random two liquid, (ELECNRTL) model. The operation conditions are varied to determine the system liquid phase stability range at the standard and critical conditions. A case study involving 30 wt% K2CO3, H2O standard system at pressure of 1 bar and temperature range from 280.15 to 366.15 K has been studied. The estimated solubility index, viscosity, water activity, and density which obtained from the simulation showed a good agreement with the experimental work. Furthermore, the saturation temperature of the solution has been estimated.

Doping Profile Measurement and Characterization by Scanning Capacitance Microscope for PocketImplanted Nano Scale n-MOSFET

This paper presents the doping profile measurement and characterization technique for the pocket implanted nano scale n-MOSFET. Scanning capacitance microscopy and atomic force microscopy have been used to image the extent of lateral dopant diffusion in MOS structures. The data are capacitance vs. voltage measurements made on a nano scale device. The technique is nondestructive when imaging uncleaved samples. Experimental data from the published literature are presented here on actual, cleaved device structures which clearly indicate the two-dimensional dopant profile in terms of a spatially varying modulated capacitance signal. Firstorder deconvolution indicates the technique has much promise for the quantitative characterization of lateral dopant profiles. The pocket profile is modeled assuming the linear pocket profiles at the source and drain edges. From the model, the effective doping concentration is found to use in modeling and simulation results of the various parameters of the pocket implanted nano scale n-MOSFET. The potential of the technique to characterize important device related phenomena on a local scale is also discussed.

A New Face Detection Technique using 2D DCT and Self Organizing Feature Map

This paper presents a new technique for detection of human faces within color images. The approach relies on image segmentation based on skin color, features extracted from the two-dimensional discrete cosine transform (DCT), and self-organizing maps (SOM). After candidate skin regions are extracted, feature vectors are constructed using DCT coefficients computed from those regions. A supervised SOM training session is used to cluster feature vectors into groups, and to assign “face" or “non-face" labels to those clusters. Evaluation was performed using a new image database of 286 images, containing 1027 faces. After training, our detection technique achieved a detection rate of 77.94% during subsequent tests, with a false positive rate of 5.14%. To our knowledge, the proposed technique is the first to combine DCT-based feature extraction with a SOM for detecting human faces within color images. It is also one of a few attempts to combine a feature-invariant approach, such as color-based skin segmentation, together with appearance-based face detection. The main advantage of the new technique is its low computational requirements, in terms of both processing speed and memory utilization.

Numerical Simulation of Wall Treatment Effects on the Micro-Scale Combustion

To understand working features of a micro combustor, a computer code has been developed to study combustion of hydrogen–air mixture in a series of chambers with same shape aspect ratio but various dimensions from millimeter to micrometer level. The prepared algorithm and the computer code are capable of modeling mixture effects in different fluid flows including chemical reactions, viscous and mass diffusion effects. The effect of various heat transfer conditions at chamber wall, e.g. adiabatic wall, with heat loss and heat conduction within the wall, on the combustion is analyzed. These thermal conditions have strong effects on the combustion especially when the chamber dimension goes smaller and the ratio of surface area to volume becomes larger. Both factors, such as larger heat loss through the chamber wall and smaller chamber dimension size, may lead to the thermal quenching of micro-scale combustion. Through such systematic numerical analysis, a proper operation space for the micro-combustor is suggested, which may be used as the guideline for microcombustor design. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the micro-combustor design, optimization and performance analysis.

An Empirical Analysis of Earnings Management in Australia

This is a comprehensive large-sample study of Australian earnings management. Using a sample of 4,844 firm-year observations across nine Australia industries from 2000 to 2006, we find substantial corporate earnings management activity across several Australian industries. We document strong evidence of size and return on assets being primary determinants of earnings management in Australia. The effects of size and return on assets are also found to be dominant in both income-increasing and incomedecreasing earnings manipulation. We also document that that periphery sector firms are more likely to involve larger magnitude of earnings management than firms in the core sector.

Color View Synthesis for Animated Depth Security X-ray Imaging

We demonstrate the synthesis of intermediary views within a sequence of color encoded, materials discriminating, X-ray images that exhibit animated depth in a visual display. During the image acquisition process, the requirement for a linear X-ray detector array is replaced by synthetic image. Scale Invariant Feature Transform, SIFT, in combination with material segmented morphing is employed to produce synthetic imagery. A quantitative analysis of the feature matching performance of the SIFT is presented along with a comparative study of the synthetic imagery. We show that the total number of matches produced by SIFT reduces as the angular separation between the generating views increases. This effect is accompanied by an increase in the total number of synthetic pixel errors. The trends observed are obtained from 15 different luggage items. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Rheological and Thermomechanical Properties of Graphene/ABS/PP Nanocomposites

In the present study, the incorporation of graphene into blends of acrylonitrile-butadiene-styrene terpolymer with polypropylene (ABS/PP) was investigated focusing on the improvement of their thermomechanical characteristics and the effect on their rheological behavior. The blends were prepared by melt mixing in a twin-screw extruder and were characterized by measuring the MFI as well as by performing DSC, TGA and mechanical tests. The addition of graphene to ABS/PP blends tends to increase their melt viscosity, due to the confinement of polymer chains motion. Also, graphene causes an increment of the crystallization temperature (Tc), especially in blends with higher PP content, because of the reduction of surface energy of PP nucleation, which is a consequence of the attachment of PP chains to the surface of graphene through the intermolecular CH-π interaction. Moreover, the above nanofiller improves the thermal stability of PP and increases the residue of thermal degradation at all the investigated compositions of blends, due to the thermal isolation effect and the mass transport barrier effect. Regarding the mechanical properties, the addition of graphene improves the elastic modulus, because of its intrinsic mechanical characteristics and its rigidity, and this effect is particularly strong in the case of pure PP.

A Rule-based Approach for Anomaly Detection in Subscriber Usage Pattern

In this report we present a rule-based approach to detect anomalous telephone calls. The method described here uses subscriber usage CDR (call detail record) data sampled over two observation periods: study period and test period. The study period contains call records of customers- non-anomalous behaviour. Customers are first grouped according to their similar usage behaviour (like, average number of local calls per week, etc). For customers in each group, we develop a probabilistic model to describe their usage. Next, we use maximum likelihood estimation (MLE) to estimate the parameters of the calling behaviour. Then we determine thresholds by calculating acceptable change within a group. MLE is used on the data in the test period to estimate the parameters of the calling behaviour. These parameters are compared against thresholds. Any deviation beyond the threshold is used to raise an alarm. This method has the advantage of identifying local anomalies as compared to techniques which identify global anomalies. The method is tested for 90 days of study data and 10 days of test data of telecom customers. For medium to large deviations in the data in test window, the method is able to identify 90% of anomalous usage with less than 1% false alarm rate.

Performance Evaluation of Hybrid Intelligent Controllers in Load Frequency Control of Multi Area Interconnected Power Systems

This paper deals with the application of artificial neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy Inference System(ANFIS) approach to Load Frequency Control (LFC) of multi unequal area hydro-thermal interconnected power system. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. Area-1 and area-2 consists of thermal reheat power plant whereas area-3 and area-4 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent controller like ANFIS, ANN and Fuzzy controllers and conventional PI and PID control approaches. To enhance the performance of intelligent and conventional controller sliding surface is included. The performances of the controllers are simulated using MATLAB/SIMULINK package. A comparison of ANFIS, ANN, Fuzzy, PI and PID based approaches shows the superiority of proposed ANFIS over ANN & fuzzy, PI and PID controller for 1% step load variation.

Hydrogeological Risk and Mining Tunnels: the Fontane-Rodoretto Mine Turin (Italy)

The interaction of tunneling or mining with groundwater has become a very relevant problem not only due to the need to guarantee the safety of workers and to assure the efficiency of the tunnel drainage systems, but also to safeguard water resources from impoverishment and pollution risk. Therefore it is very important to forecast the drainage processes (i.e., the evaluation of drained discharge and drawdown caused by the excavation). The aim of this study was to know better the system and to quantify the flow drained from the Fontane mines, located in Val Germanasca (Turin, Italy). This allowed to understand the hydrogeological local changes in time. The work has therefore been structured as follows: the reconstruction of the conceptual model with the geological, hydrogeological and geological-structural study; the calculation of the tunnel inflows (through the use of structural methods) and the comparison with the measured flow rates; the water balance at the basin scale. In this way it was possible to understand what are the relationships between rainfall, groundwater level variations and the effect of the presence of tunnels as a means of draining water. Subsequently, it the effects produced by the excavation of the mining tunnels was quantified, through numerical modeling. In particular, the modeling made it possible to observe the drawdown variation as a function of number, excavation depth and different mines linings.

Thermogravimetry Study on Pyrolysis of Various Lignocellulosic Biomass for Potential Hydrogen Production

This paper aims to study decomposition behavior in pyrolytic environment of four lignocellulosic biomass (oil palm shell, oil palm frond, rice husk and paddy straw), and two commercial components of biomass (pure cellulose and lignin), performed in a thermogravimetry analyzer (TGA). The unit which consists of a microbalance and a furnace flowed with 100 cc (STP) min-1 Nitrogen, N2 as inert. Heating rate was set at 20⁰C min-1 and temperature started from 50 to 900⁰C. Hydrogen gas production during the pyrolysis was observed using Agilent Gas Chromatography Analyzer 7890A. Oil palm shell, oil palm frond, paddy straw and rice husk were found to be reactive enough in a pyrolytic environment of up to 900°C since pyrolysis of these biomass starts at temperature as low as 200°C and maximum value of weight loss is achieved at about 500°C. Since there was not much different in the cellulose, hemicelluloses and lignin fractions between oil palm shell, oil palm frond, paddy straw and rice husk, the T-50 and R-50 values obtained are almost similar. H2 productions started rapidly at this temperature as well due to the decompositions of biomass inside the TGA. Biomass with more lignin content such as oil palm shell was found to have longer duration of H2 production compared to materials of high cellulose and hemicelluloses contents.

On the Fast Convergence of DD-LMS DFE Using a Good Strategy Initialization

In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence.

Necessity of Risk Management of Various Industry-Associated Pollutants(Case Study of Gavkhoni Wetland Ecosystem)

Since the beginning of human history, human activities have caused many changes in the environment. Today, a particular attention should be paid to gaining knowledge about water quality of wetlands which are pristine natural environments rich in genetic reserves. If qualitative conditions of industrial areas (in terms of both physicochemical and biological conditions) are not addressed properly, they could cause disruption in natural ecosystems, especially in rivers. With regards to the quality of water resources, determination of pollutant sources plays a pivotal role in engineering projects as well as designing water quality control systems. Thus, using different methods such as flow duration curves, dischargepollution load model and frequency analysis by HYFA software package, risk of various industrial pollutants in international and ecologically important Gavkhoni wetland is analyzed. In this study, a station located at Varzaneh City is used as the last station on Zayanderud River, from where the river water is discharged into the wetland. Results showed that elements- concentrations often exceeded the allowed level and river water can endanger regional ecosystem. In addition, if the river discharge is managed on Q25 basis, this basis can lower concentrations of elements, keeping them within the normal level.

Concept of Automation in Management of Electric Power Systems

An electric power system includes a generating, a transmission, a distribution, and consumers subsystems. An electrical power network in Tanzania keeps growing larger by the day and become more complex so that, most utilities have long wished for real-time monitoring and remote control of electrical power system elements such as substations, intelligent devices, power lines, capacitor banks, feeder switches, fault analyzers and other physical facilities. In this paper, the concept of automation of management of power systems from generation level to end user levels was determined by using Power System Simulator for Engineering (PSS/E) version 30.3.2.