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.

Integration Methods and Processes of Product Design and Flexible Production for Direct Production within the iCIM 3000 System

Currently is characterized production engineering together with the integration of industrial automation and robotics such very quick view of to manufacture the products. The production range is continuously changing, expanding and producers have to be flexible in this regard. It means that need to offer production possibilities, which can respond to the quick change. Engineering product development is focused on supporting CAD software, such systems are mainly used for product design. That manufacturers are competitive, it should be kept procured machines made available capable of responding to output flexibility. In response to that problem is the development of flexible manufacturing systems, consisting of various automated systems. The integration of flexible manufacturing systems and subunits together with product design and of engineering is a possible solution for this issue. Integration is possible through the implementation of CIM systems. Such a solution and finding a hyphen between CAD and procurement system ICIM 3000 from Festo Co. is engaged in the research project and this contribution. This can be designed the products in CAD systems and watch the manufacturing process from order to shipping by the development of methods and processes of integration, This can be modeled in CAD systems products and watch the manufacturing process from order to shipping to develop methods and processes of integration, which will improve support for product design parameters by monitoring of the production process, by creating of programs for production using the CAD and therefore accelerates the a total of process from design to implementation.

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 Heuristics Approach for Fast Detecting Suspicious Money Laundering Cases in an Investment Bank

Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most international financial institutions have been implementing anti-money laundering solutions (AML) to fight investment fraud. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project for the purpose of developing a new solution for the AML Units in an international investment bank, we proposed a data mining-based solution for AML. In this paper, we present a heuristics approach to improve the performance for this solution. We also show some preliminary results associated with this method on analysing transaction datasets.

Traveling Wave Solutions for the (3+1)-Dimensional Breaking Soliton Equation by (G'/G)- Expansion Method and Modified F-Expansion Method

In this paper, using (G/G )-expansion method and modified F-expansion method, we give some explicit formulas of exact traveling wave solutions for the (3+1)-dimensional breaking soliton equation. A modified F-expansion method is proposed by taking full advantages of F-expansion method and Riccati equation in seeking exact solutions of the equation.

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.

Developing Damage Assessment Model for Bridge Surroundings: A Study of Disaster by Typhoon Morakot in Taiwan

This paper presents an integrated model that automatically measures the change of rivers, damage area of bridge surroundings, and change of vegetation. The proposed model is on the basis of a neurofuzzy mechanism enhanced by SOM optimization algorithm, and also includes three functions to deal with river imagery. High resolution imagery from FORMOSAT-2 satellite taken before and after the invasion period is adopted. By randomly selecting a bridge out of 129 destroyed bridges, the recognition results show that the average width has increased 66%. The ruined segment of the bridge is located exactly at the most scour region. The vegetation coverage has also reduced to nearly 90% of the original. The results yielded from the proposed model demonstrate a pinpoint accuracy rate at 99.94%. This study brings up a successful tool not only for large-scale damage assessment but for precise measurement to disasters.

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.

Investigation of Genetic Epidemiology of Metabolic Compromises in ß Thalassemia Minor Mutation: Phenotypic Pleiotropy

Human genome is not only the evolutionary summation of all advantageous events, but also houses lesions of deleterious foot prints. A single gene mutation sometimes may express multiple consequences in numerous tissues and a linear relationship of the genotype and the phenotype may often be obscure. ß Thalassemia minor, a transfusion independent mild anaemia, coupled with environment among other factors may articulate into phenotypic pleotropy with Hypocholesterolemia, Vitamin D deficiency, Tissue hypoxia, Hyper-parathyroidism and Psychological alterations. Occurrence of Pancreatic insufficiency, resultant steatorrhoea, Vitamin-D (25-OH) deficiency (13.86 ngm/ml) with Hypocholesterolemia (85mg/dl) in a 30 years old male ß Thal-minor patient (Hemoglobin 11mg/dl with Fetal Hemoglobin 2.10%, Hb A2 4.60% and Hb Adult 84.80% and altered Hemogram) with increased Para thyroid hormone (62 pg/ml) & moderate Serum Ca+2 (9.5mg/ml) indicate towards a cascade of phenotypic pleotropy where the ß Thalassemia mutation ,be it in the 5’ cap site of the mRNA , differential splicing etc in heterozygous state is effecting several metabolic pathways. Compensatory extramedulary hematopoiesis may not coped up well with the stressful life style of the young individual and increased erythropoietic stress with high demand for cholesterol for RBC membrane synthesis may have resulted in Hypocholesterolemia.Oxidative stress and tissue hypoxia may have caused the pancreatic insufficiency, leading to Vitamin D deficiency. This may in turn have caused the secondary hyperparathyroidism to sustain serum Calcium level. Irritability and stress intolerance of the patient was a cumulative effect of the vicious cycle of metabolic compromises. From these findings we propose that the metabolic deficiencies in the ß Thalassemia mutations may be considered as the phenotypic display of the pleotropy to explain the genetic epidemiology. According to the recommendations from the NIH Workshop on Gene-Environment Interplay in Common Complex Diseases: Forging an Integrative Model, study design of observations should be informed by gene-environment hypotheses and results of a study (genetic diseases) should be published to inform future hypotheses. Variety of approaches is needed to capture data on all possible aspects, each of which is likely to contribute to the etiology of disease. Speakers also agreed that there is a need for development of new statistical methods and measurement tools to appraise information that may be missed out by conventional method where large sample size is needed to segregate considerable effect. A meta analytic cohort study in future may bring about significant insight on to the title comment.

Absence of Leave and Job Morality in the ICU

Leave of absence is important in maintaining a good status of human resource quality. Allowing the employees temporarily free from the routine assignments can vitalize the workers- morality and productivity. This is particularly critical to secure a satisfactory service quality for healthcare professionals of which were typically featured with labor intensive and complicated works to perform. As one of the veteran hospitals that were found and operated by the Veteran Department of Taiwan, the nursing staff of the case hospital was squeezed to an extreme minimum level under the pressure of a tight budgeting. Leave of absence on schedule became extremely difficult, especially for the intensive care units (ICU), in which required close monitoring over the cared patients, and that had more easily driven the ICU nurses nervous. Even worse, the deferred leaves were more than 10 days at any time in the ICU because of a fluctuating occupancy. As a result, these had brought a bad setback to this particular nursing team, and consequently defeated the job performance and service quality. To solve this problem and accordingly to strengthen their morality, a project team was organized across different departments specific for this. Sufficient information regarding jobs and positions requirements, labor resources, and actual working hours in detail were collected and analyzed in the team meetings. Several alternatives were finalized. These included job rotating, job combination, leave on impromptu and cross-departmental redeployment. Consequently, the deferred leave days sharply reduced 70% to a level of 3 or less days. This improvement had not only provided good shelter for the ICU nurses that improved their job performance and patient safety but also encouraged the nurses active participating of a project and learned the skills of solving problems with colleagues.

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.

Comparison of Different Neural Network Approaches for the Prediction of Kidney Dysfunction

This paper presents the prediction of kidney dysfunction using different neural network (NN) approaches. Self organization Maps (SOM), Probabilistic Neural Network (PNN) and Multi Layer Perceptron Neural Network (MLPNN) trained with Back Propagation Algorithm (BPA) are used in this study. Six hundred and sixty three sets of analytical laboratory tests have been collected from one of the private clinical laboratories in Baghdad. For each subject, Serum urea and Serum creatinin levels have been analyzed and tested by using clinical laboratory measurements. The collected urea and cretinine levels are then used as inputs to the three NN models in which the training process is done by different neural approaches. SOM which is a class of unsupervised network whereas PNN and BPNN are considered as class of supervised networks. These networks are used as a classifier to predict whether kidney is normal or it will have a dysfunction. The accuracy of prediction, sensitivity and specificity were found for each type of the proposed networks .We conclude that PNN gives faster and more accurate prediction of kidney dysfunction and it works as promising tool for predicting of routine kidney dysfunction from the clinical laboratory data.

Numerical Analysis of Concrete Crash Barriers

Reinforced concrete crash barriers used in road traffic must meet a number of criteria. Crash barriers are laid lengthwise, one behind another, and joined using specially designed steel locks. While developing BSV reinforced concrete crash barriers (type ŽPSV), experiments and calculations aimed to optimize the shape of a newly designed lock and the reinforcement quantity and distribution in a crash barrier were carried out. The tension carrying capacity of two parallelly joined locks was solved experimentally. Based on the performed experiments, adjustments of nonlinear properties of steel were performed in the calculations. The obtained results served as a basis to optimize the lock design using a computational model that takes into account the plastic behaviour of steel and the influence of the surrounding concrete [6]. The response to the vehicle impact has been analyzed using a specially elaborated complex computational model, comprising both the nonlinear model of the damping wall or crash barrier and the detailed model of the vehicle [7].

A New Precautionary Method for Measurement and Improvement the Data Quality

the data quality is a kind of complex and unstructured concept, which is concerned by information systems managers. The reason of this attention is the high amount of Expenses for maintenance and cleaning of the inefficient data. Such a data more than its expenses of lack of quality, cause wrong statistics, analysis and decisions in organizations. Therefor the managers intend to improve the quality of their information systems' data. One of the basic subjects of quality improvement is the evaluation of the amount of it. In this paper, we present a precautionary method, which with its application the data of information systems would have a better quality. Our method would cover different dimensions of data quality; therefor it has necessary integrity. The presented method has tested on three dimensions of accuracy, value-added and believability and the results confirm the improvement and integrity of this method.

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.

Significance of Splitting Method in Non-linear Grid system for the Solution of Navier-Stokes Equation

Solution to unsteady Navier-Stokes equation by Splitting method in physical orthogonal algebraic curvilinear coordinate system, also termed 'Non-linear grid system' is presented. The linear terms in Navier-Stokes equation are solved by Crank- Nicholson method while the non-linear term is solved by the second order Adams-Bashforth method. This work is meant to bring together the advantage of Splitting method as pressure-velocity solver of higher efficiency with the advantage of consuming Non-linear grid system which produce more accurate results in relatively equal number of grid points as compared to Cartesian grid. The validation of Splitting method as a solution of Navier-Stokes equation in Nonlinear grid system is done by comparison with the benchmark results for lid driven cavity flow by Ghia and some case studies including Backward Facing Step Flow Problem.

An Advanced Hybrid P2p Botnet 2.0

Recently, malware attacks have become more serious over the Internet by e-mail, denial of service (DoS) or distributed denial of service (DDoS). The Botnets have become a significant part of the Internet malware attacks. The traditional botnets include three parts – botmaster, command and control (C&C) servers and bots. The C&C servers receive commands from botmaster and control the distributions of computers remotely. Bots use DNS to find the positions of C&C server. In this paper, we propose an advanced hybrid peer-to-peer (P2P) botnet 2.0 (AHP2P botnet 2.0) using web 2.0 technology to hide the instructions from botmaster into social sites, which are regarded as C&C servers. Servent bots are regarded as sub-C&C servers to get the instructions from social sites. The AHP2P botnet 2.0 can evaluate the performance of servent bots, reduce DNS traffics from bots to C&C servers, and achieve harder detection bots actions than IRC-based botnets over the Internet.

Analysis of Residual Strain and Stress Distributions in High Speed Milled Specimens using an Indentation Method

Through a proper analysis of residual strain and stress distributions obtained at the surface of high speed milled specimens of AA 6082–T6 aluminium alloy, the performance of an improved indentation method is evaluated. This method integrates a special device of indentation to a universal measuring machine. The mentioned device allows introducing elongated indents allowing to diminish the absolute error of measurement. It must be noted that the present method offers the great advantage of avoiding both the specific equipment and highly qualified personnel, and their inherent high costs. In this work, the cutting tool geometry and high speed parameters are selected to introduce reduced plastic damage. Through the variation of the depth of cut, the stability of the shapes adopted by the residual strain and stress distributions is evaluated. The results show that the strain and stress distributions remain unchanged, compressive and small. Moreover, these distributions reveal a similar asymmetry when the gradients corresponding to conventional and climb cutting zones are compared.

Approximating Maximum Weighted Independent Set Using Vertex Support

The Maximum Weighted Independent Set (MWIS) problem is a classic graph optimization NP-hard problem. Given an undirected graph G = (V, E) and weighting function defined on the vertex set, the MWIS problem is to find a vertex set S V whose total weight is maximum subject to no two vertices in S are adjacent. This paper presents a novel approach to approximate the MWIS of a graph using minimum weighted vertex cover of the graph. Computational experiments are designed and conducted to study the performance of our proposed algorithm. Extensive simulation results show that the proposed algorithm can yield better solutions than other existing algorithms found in the literature for solving the MWIS.

Application of Extreme Learning Machine Method for Time Series Analysis

In this paper, we study the application of Extreme Learning Machine (ELM) algorithm for single layered feedforward neural networks to non-linear chaotic time series problems. In this algorithm the input weights and the hidden layer bias are randomly chosen. The ELM formulation leads to solving a system of linear equations in terms of the unknown weights connecting the hidden layer to the output layer. The solution of this general system of linear equations will be obtained using Moore-Penrose generalized pseudo inverse. For the study of the application of the method we consider the time series generated by the Mackey Glass delay differential equation with different time delays, Santa Fe A and UCR heart beat rate ECG time series. For the choice of sigmoid, sin and hardlim activation functions the optimal values for the memory order and the number of hidden neurons which give the best prediction performance in terms of root mean square error are determined. It is observed that the results obtained are in close agreement with the exact solution of the problems considered which clearly shows that ELM is a very promising alternative method for time series prediction.