Search results for: Optimal Normal Basis

Authors: Priyanka Paliwal, N.P. Patidar

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Distributed Power generation has gained a lot of attention in recent times due to constraints associated with conventional power generation and new advancements in DG technologies .The need to operate the power system economically and with optimum levels of reliability has further led to an increase in interest in Distributed Generation. However it is important to place Distributed Generator on an optimum location so that the purpose of loss minimization and voltage regulation is dully served on the feeder. This paper investigates the impact of DG units installation on electric losses, reliability and voltage profile of distribution networks. In this paper, our aim would be to find optimal distributed generation allocation for loss reduction subjected to constraint of voltage regulation in distribution network. The system is further analyzed for increased levels of Reliability. Distributed Generator offers the additional advantage of increase in reliability levels as suggested by the improvements in various reliability indices such as SAIDI, CAIDI and AENS. Comparative studies are performed and related results are addressed. An analytical technique is used in order to find the optimal location of Distributed Generator. The suggested technique is programmed under MATLAB software. The results clearly indicate that DG can reduce the electrical line loss while simultaneously improving the reliability of the system.

Keywords: AENS, CAIDI, Distributed Generation, lossreduction, Reliability, SAIDI

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Authors: Mustafa M. Donma, Orkide Donma

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A growing list of cancers might be influenced by obesity. Obesity is associated with an increased risk for the occurrence and development of some cancers. Inflammation can lead to cancer. It is one of the characteristic features of cancer and plays a critical role in cancer development. C-reactive protein (CRP) is under evaluation related to the new and simple prognostic factors in patients with metastatic renal cell cancer. Obesity can predict and promote systemic inflammation in healthy adults. BMI is correlated with hs-CRP. In this study, SII index and CRP values were evaluated in children with normal BMI and those within the range of different obesity grades to detect the tendency towards cancer in pediatric obesity. A total of one hundred and ninety-four children; thirty-five children with normal BMI, twenty overweight (OW), forty-seven obese (OB) and ninety-two morbid obese (MO) participated in the study. Age- and sex-matched groups were constituted using BMI-for age percentiles. Informed consent was obtained. Ethical Committee approval was taken. Weight, height, waist circumference (C), hip C, head C and neck C of the children were measured. The complete blood count test was performed. C-reactive protein analysis was performed. Statistical analyses were performed using SPSS. The degree for statistical significance was p≤0.05. SII index values were progressively increasing starting from normal weight (NW) to MO children. There is a statistically significant difference between NW and OB as well as MO children. No significant difference was observed between NW and OW children, however, a correlation was observed between NW and OW children. MO constitutes the only group, which exhibited a statistically significant correlation between SII index and CRP. Obesity-related bladder, kidney, cervical, liver, colorectal, endometrial cancers are still being investigated. Obesity, characterized as a chronic low-grade inflammation, is a crucial risk factor for colon cancer. Elevated childhood BMI values may be indicative of processes leading to cancer, initiated early in life. Prevention of childhood adiposity may decrease the cancer incidence in adults. To authors’ best knowledge, this study is the first to introduce SII index values during obesity of varying degrees of severity. It is suggested that this index seems to affect all stages of obesity with an increasing tendency and may point out the concomitant status of obesity and cancer starting from very early periods of life.

Keywords: Children, c- reactive protein, systemic immune-inflammation index, obesity.

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Authors: Ritu Vijay, Rekha Govil

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The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.

Keywords: ANN, RBF, Tidal Data.

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Authors: Sreejith Jayachandran, Mojtaba Ghodsi, Morteza Mohammadzaheri

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The modern busy world is running behind new embedded technologies based on computers and software meanwhile some people are unable to monitor their health condition and regular medical check-ups. Some of them postpone medical check-ups due to a lack of time and convenience while others skip these regular evaluations and medical examinations due to huge medical bills and hospital expenses. In this research, we present a device in the telemonitoring system capable of monitoring, checking, and evaluating the health status of the human body remotely through the internet for the needs of all kinds of people. The remote health monitoring device is a microcontroller-based embedded unit. The various types of sensors in this device are connected to the human body, and with the help of an Arduino UNO board, the required analogue data are collected from the sensors. The microcontroller on the Arduino board processes the analogue data collected in this way into digital data and transfers that information to the cloud and stores it there; the processed digital data are then instantly displayed through the LCD attached to the machine. By accessing the cloud storage with a username and password, the concerned person’s health care teams/doctors, and other health staff can collect these data for the assessment and follow-up of that patient. Besides that, the family members/guardians can use and evaluate these data for awareness of the patient's current health status. Moreover, the system is connected to a GPS module. In emergencies, the concerned team can be positioning the patient or the person with this device. The setup continuously evaluates and transfers the data to the cloud and also the user can prefix a normal value range for the evaluation. For example, the blood pressure normal value is universally prefixed between 80/120 mmHg. Similarly, the Remote Health Monitoring System (RHMS) is also allowed to fix the range of values referred to as normal coefficients. This IoT-based miniature system 11×10×10 cm3 with a low weight of 500 gr only consumes 10 mW. This smart monitoring system is manufactured for 100 GBP (British Pound Sterling), and can facilitate the communication between patients and health systems, but also it can be employed for numerous other uses including communication sectors in the aerospace and transportation systems.

Keywords: Embedded Technology, Telemonitoring system, Microcontroller, Arduino UNO, Cloud storage, GPS, RHMS, Remote Health Monitoring System, Alert system.

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Authors: Sadia Iqbal, Faheem Iqbal, Furqan Iqbal

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Efficient utilization of existing water is a pressing need for Pakistan. Due to rising population, reduction in present storage capacity and poor delivery efficiency of 30 to 40% from canal. A study to evaluate an irrigation system in the cotton-wheat zone of Pakistan, after the watercourse lining was conducted. The study is made on the basis of cropping pattern and salinity to evaluate the system. This study employed an index-based approach of using Geographic information system with field data. The satellite images of different years were use to examine the effective area. Several combinations of the ratio of signals received in different spectral bands were used for development of this index. Near Infrared and Thermal IR spectral bands proved to be most effective as this combination helped easy detection of salt affected area and cropping pattern of the study area. Result showed that 9.97% area under salinity in 1992, 9.17% in 2000 and it left 2.29% in year 2005. Similarly in 1992, 45% area is under vegetation it improves to 56% and 65% in 2000 and 2005 respectively. On the basis of these results evaluation is done 30% performance is increase after the watercourse improvement.

Keywords: Salinity, remote sensing index, salinity index, cropping pattern.

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Authors: Ahmed Aljudaya, Derek Ingham, Lin Ma, Kevin Hughes, Mohammed Pourkashanian

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Researchers, power companies, and state politicians have given concentrated solar power (CSP) much attention due to its capacity to generate large amounts of electricity whereas overcoming the intermittent nature of solar resources. The Linear Fresnel Reflector (LFR) is a well-known CSP technology type for being inexpensive, having a low land use factor, and suffering from low optical efficiency. The LFR was considered a cost-effective alternative option to the Parabolic Trough Collector (PTC) because of its simplistic design, and this often outweighs its lower efficiency. The LFR power plants commercially generate steam directly and indirectly in order to produce electricity with high technical efficiency and lower its costs. The purpose of this important analysis is to compare the annual performance of the Direct Steam Generation (DSG) and Indirect Steam Generation (ISG) of LFR power plants using molten salt and other different Heat Transfer Fluids (HTF) to investigate their technical and economic effects. A 50 MWe solar-only system is examined as a case study for both steam production methods in extreme weather conditions. In addition, a parametric analysis is carried out to determine the optimal solar field size that provides the lowest Levelized Cost of Electricity (LCOE) while achieving the highest technical performance. As a result of optimizing the optimum solar field size, the solar multiple (SM) is found to be between 1.2 – 1.5 in order to achieve as low as 9 Cent/KWh for the DSG of the LFR. In addition, the power plant is capable of producing around 141 GWh annually and up to 36% of the capacity factor, whereas the ISG produces less energy at a higher cost. The optimization results show that the DSG’s performance overcomes the ISG in producing around 3% more annual energy, 2% lower LCOE, and 28% less capital cost.

Keywords: Concentrated Solar Power, Levelized cost of electricity, Linear Fresnel reflectors, Steam generation.

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: Artificial Neural Network, Taguchi Method, Real Estate Valuation Model.

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Authors: Pegah Farshadmanesh, Jamshid Mohammadi, Mehdi Modares

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In nearly all earthquakes of the past century that resulted in moderate to significant damage, the occurrence of postearthquake fire ignition (PEFI) has imposed a serious hazard and caused severe damage, especially in urban areas. In order to reduce the loss of life and property caused by post-earthquake fires, there is a crucial need for predictive models to estimate the PEFI risk. The parameters affecting PEFI risk can be categorized as: 1) factors influencing fire ignition in normal (non-earthquake) condition, including floor area, building category, ignitability, type of appliance, and prevention devices, and 2) earthquake related factors contributing to the PEFI risk, including building vulnerability and earthquake characteristics such as intensity, peak ground acceleration, and peak ground velocity. State-of-the-art statistical PEFI risk models are solely based on limited available earthquake data, and therefore they cannot predict the PEFI risk for areas with insufficient earthquake records since such records are needed in estimating the PEFI model parameters. In this paper, the correlation between normal condition ignition risk, peak ground acceleration, and PEFI risk is examined in an effort to offer a means for predicting post-earthquake ignition events. An illustrative example is presented to demonstrate how such correlation can be employed in a seismic area to predict PEFI hazard.

Keywords: Fire risk, post-earthquake fire ignition (PEFI), risk management, seismicity.

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Authors: Dmitry Yu. Korulkin, Raissa A. Muzychkina, Evgenii N. Kojaev

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In review the generalized data about biological activity of anthraquinone-containing plants and specimens on their basis is presented. Data of traditional medicine, results of bioscreening and clinical researches of specimens are analyzed.

Keywords: Anthraquinones, physiologically active substances, phytopreparation, Ramon.

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Authors: P. Slepicka, N. Slepickova Kasalkova, I. Michaljanicova, O. Nedela, Z. Kolska, V. Svorcik

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Polymers exposed to laser or plasma treatment or modified with different wet methods which enable the introduction of nanoparticles or biologically active species, such as amino-acids, may find many applications both as biocompatible or anti-bacterial materials or on the contrary, can be applied for a decrease in the number of cells on the treated surface which opens application in single cell units. For the experiments, two types of materials were chosen, a representative of non-biodegradable polymers, polyethersulphone (PES) and polyhydroxybutyrate (PHB) as biodegradable material. Exposure of solid substrate to laser well below the ablation threshold can lead to formation of various surface structures. The ripples have a period roughly comparable to the wavelength of the incident laser radiation, and their dimensions depend on many factors, such as chemical composition of the polymer substrate, laser wavelength and the angle of incidence. On the contrary, biopolymers may significantly change their surface roughness and thus influence cell compatibility. The focus was on the surface treatment of PES and PHB by pulse excimer KrF laser with wavelength of 248 nm. The changes of physicochemical properties, surface morphology, surface chemistry and ablation of exposed polymers were studied both for PES and PHB. Several analytical methods involving atomic force microscopy, gravimetry, scanning electron microscopy and others were used for the analysis of the treated surface. It was found that the combination of certain input parameters leads not only to the formation of optimal narrow pattern, but to the combination of a ripple and a wrinkle-like structure, which could be an optimal candidate for cell attachment. The interaction of different types of cells and their interactions with the laser exposed surface were studied. It was found that laser treatment contributes as a major factor for wettability/contact angle change. The combination of optimal laser energy and pulse number was used for the construction of a surface with an anti-cellular response. Due to the simple laser treatment, we were able to prepare a biopolymer surface with higher roughness and thus significantly influence the area of growth of different types of cells (U-2 OS cells).

Keywords: Polymer treatment, laser, periodic pattern, cell response.

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: Information Gain (IG), Intrusion Detection System (IDS), K-means Clustering, Weka.

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Authors: Ayad Salih Sabbar, Amin Chegenizadeh, Hamid Nikraz

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Utilizing waste materials in civil engineering applications has a positive influence on the environment by reducing carbon dioxide emissions and issues associated with waste disposal. Granulated blast furnace slag (GBFS) is a by-product of the iron and steel industry, with millions of tons of slag being annually produced worldwide. Slag has been widely used in structural engineering and for stabilizing clay soils; however, studies on the effect of slag on sandy soils are scarce. This article investigates the effect of slag content on shear strength parameters through direct shear tests and unconsolidated undrained triaxial tests on mixtures of Perth sand and slag. For this purpose, sand-slag mixtures, with slag contents of 2%, 4%, and 6% by weight of samples, were tested with direct shear tests under three normal stress values, namely 100 kPa, 150 kPa, and 200 kPa. Unconsolidated undrained triaxial tests were performed under a single confining pressure of 100 kPa and relative density of 80%. The internal friction angles and shear stresses of the mixtures were determined via the direct shear tests, demonstrating that shear stresses increased with increasing normal stress and the internal friction angles and cohesion increased with increasing slag. There were no significant differences in shear stresses parameters when slag content rose from 4% to 6%. The unconsolidated undrained triaxial tests demonstrated that shear strength increased with increasing slag content.

Keywords: Direct shear, shear strength, slag, UU test.

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Authors: Matthias Dehmer, Frank Emmert Streib, Jürgen Kilian, Andreas Zulauf

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Methods for organizing web data into groups in order to analyze web-based hypertext data and facilitate data availability are very important in terms of the number of documents available online. Thereby, the task of clustering web-based document structures has many applications, e.g., improving information retrieval on the web, better understanding of user navigation behavior, improving web users requests servicing, and increasing web information accessibility. In this paper we investigate a new approach for clustering web-based hypertexts on the basis of their graph structures. The hypertexts will be represented as so called generalized trees which are more general than usual directed rooted trees, e.g., DOM-Trees. As a important preprocessing step we measure the structural similarity between the generalized trees on the basis of a similarity measure d. Then, we apply agglomerative clustering to the obtained similarity matrix in order to create clusters of hypertext graph patterns representing navigation structures. In the present paper we will run our approach on a data set of hypertext structures and obtain good results in Web Structure Mining. Furthermore we outline the application of our approach in Web Usage Mining as future work.

Keywords: Clustering methods, graph-based patterns, graph similarity, hypertext structures, web structure mining

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Authors: Surasak Siripornadulsil, Nutt Poomai, Wilailak Siripornadulsil

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Due to a high ethanol demand, the approach for  effective ethanol production is important and has been developed  rapidly worldwide. Several agricultural wastes are highly  abundant in celluloses and the effective cellulase enzymes do exist  widely among microorganisms. Accordingly, the cellulose  degradation using microbial cellulase to produce a low-cost substrate  for ethanol production has attracted more attention. In this  study, the cellulase producing bacterial strain has been isolated  from rich straw and identified by 16S rDNA sequence analysis as Acinetobacter sp. KKU44. This strain is able to grow and exhibit the cellulase activity. The optimal temperature for its growth and  cellulase production is 37°C. The optimal temperature of bacterial  cellulase activity is 60°C. The cellulase enzyme from  Acinetobacter sp. KKU44 is heat-tolerant enzyme. The bacterial culture of 36h. showed highest cellulase activity at 120U/mL when  grown in LB medium containing 2% (w/v). The capability of  Acinetobacter sp. KKU44 to grow in cellulosic agricultural wastes as a sole carbon source and exhibiting the high cellulase activity at high temperature suggested that this strain could be potentially developed further as a cellulose degrading strain for a production of low-cost substrate used in ethanol production. 

 

Keywords: Acinetobacter sp. KKU44, bagasse, cellulase enzyme, rice husk.

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Authors: Taiki Baba, Tomoaki Hashimoto

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The random dither quantization method enables us to achieve much better performance than the simple uniform quantization method for the design of quantized control systems. Motivated by this fact, the stochastic model predictive control method in which a performance index is minimized subject to probabilistic constraints imposed on the state variables of systems has been proposed for linear feedback control systems with random dither quantization. In other words, a method for solving optimal control problems subject to probabilistic state constraints for linear discrete-time control systems with random dither quantization has been already established. To our best knowledge, however, the feasibility of such a kind of optimal control problems has not yet been studied. Our objective in this paper is to investigate the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization. To this end, we provide the results of numerical simulations that verify the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization.

Keywords: Model predictive control, stochastic systems, probabilistic constraints, random dither quantization.

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Authors: V. R. Ahire, A. Kumar, B. N. Pandey, K. P. Mishra, G. R. Kulkarni

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Radiation therapy is an effective vital strategy used globally in the treatment of cervical cancer. However, radiation efficacy principally depends on the radiosensitivity of the tumor, and not all patient exhibit significant response to irradiation. A radiosensitive tumor is easier to cure than a radioresistant tumor which later advances to local recurrence and metastasis. Herbal polyphenols are gaining attention for exhibiting radiosensitization through various signaling. Current work focuses to study the radiosensitization effect of ellagic acid (EA), on HeLa cells. EA intermediated radiosensitization of HeLa cells was due to the induction γ-H2AX foci formation, G1 phase cell cycle arrest, and loss of reproductive potential, growth inhibition, drop in the mitochondrial membrane potential and protein expression studies that eventually induced apoptosis. Irradiation of HeLa in presence of EA (10 μM) to doses of 2 and 4 Gy γ-radiation produced marked tumor cytotoxicity. EA also demonstrated radio-protective effect on normal cell, NIH3T3 and aided recovery from the radiation damage. Our results advocate EA to be an effective adjuvant for improving cancer radiotherapy as it displays striking tumor cytotoxicity and reduced normal cell damage instigated by irradiation.

Keywords: Apoptotic radiosensitivity, ellagic acid, mitochondrial potential, cell-cycle arrest.

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Authors: MP. Mulaudzi, MA. Petersen, J. Mukuddem-Petersen , IM. Schoeman, B. de Waal, JM. Manale

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This conference paper discusses a risk allocation problem for subprime investing banks involving investment in subprime structured mortgage products (SMPs) and Treasuries. In order to solve this problem, we develop a L'evy process-based model of jump diffusion-type for investment choice in subprime SMPs and Treasuries. This model incorporates subprime SMP losses for which credit default insurance in the form of credit default swaps (CDSs) can be purchased. In essence, we solve a mean swap-at-risk (SaR) optimization problem for investment which determines optimal allocation between SMPs and Treasuries subject to credit risk protection via CDSs. In this regard, SaR is indicative of how much protection investors must purchase from swap protection sellers in order to cover possible losses from SMP default. Here, SaR is defined in terms of value-at-risk (VaR). Finally, we provide an analysis of the aforementioned optimization problem and its connections with the subprime mortgage crisis (SMC).

Keywords: Investors; Jump Diffusion Process, Structured Mortgage Products, Treasuries, Credit Risk, Credit Default Swaps, Tranching Risk, Counterparty Risk, Value-at-Risk, Swaps-at-Risk, Subprime Mortgage Crisis.

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Authors: Yuan-Kang Shih, Shu-Li Chang, Shin-Shin Kao

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Qk n has been shown as an alternative to the hypercube family. For any even integer k ≥ 4 and any integer n ≥ 2, Qk n is a bipartite graph. In this paper, we will prove that given any pair of vertices, w and b, from different partite sets of Qk n, there exist 2n internally disjoint paths between w and b, denoted by {Pi | 0 ≤ i ≤ 2n-1}, such that 2n-1 i=0 Pi covers all vertices of Qk n. The result is optimal since each vertex of Qk n has exactly 2n neighbors.

Keywords: container, Hamiltonian, k-ary n-cube, m*-connected.

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Authors: Malinwo Estone Ayikpa

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Electric power systems are likely to operate with minimum losses and voltage meeting international standards. This is made possible generally by control actions provide by automatic voltage regulators, capacitors and transformers with on-load tap changer (OLTC). With the development of photovoltaic (PV) systems technology, their integration on distribution networks has increased over the last years to the extent of replacing the above mentioned techniques. The conventional analysis and simulation tools used for electrical networks are no longer able to take into account control actions necessary for studying distributed PV generation impact. This paper presents an unbalanced optimal power flow (OPF) model that minimizes losses with association of active power generation and reactive power control of single-phase and three-phase PV systems. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The unbalance OPF is formulated by current balance equations and solved by primal-dual interior point method. Several simulation cases have been carried out varying the size and location of PV systems and the results show a detailed view of the impact of PV distributed generation on distribution systems.

Keywords: Distribution system, losses, photovoltaic generation, primal-dual interior point method, reactive power control.

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Authors: Najmeh Bolbolamiri, Maryam Setayesh Sanai, Ahmad Mirabadi

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This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.

Keywords: stator currents monitoring, railway points, point failures, fault detection and diagnosis, Kolmogorov-Smirnov test, time-domain analysis.

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Authors: Nooshin Salari, Viliam Makis, Jane Doe

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This paper presents a maintenance policy for a system consisting of two units. Unit 1 is gradually deteriorating and is subject to soft failure. Unit 2 has a general lifetime distribution and is subject to hard failure. Condition of unit 1 of the system is monitored periodically and it is considered as failed when its deterioration level reaches or exceeds a critical level N. At the failure time of unit 2 system is considered as failed, and unit 2 will be correctively replaced by the next inspection epoch. Unit 1 or 2 are preventively replaced when deterioration level of unit 1 or age of unit 2 exceeds the related preventive maintenance (PM) levels. At the time of corrective or preventive replacement of unit 2, there is an opportunity to replace unit 1 if its deterioration level reaches the opportunistic maintenance (OM) level. If unit 2 fails in an inspection interval, system stops operating although unit 1 has not failed. A mathematical model is derived to find the preventive and opportunistic replacement levels for unit 1 and preventive replacement age for unit 2, that minimize the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. Numerical example is provided to illustrate the performance of the proposed model and the comparison of the proposed model with an optimal policy without opportunistic maintenance level for unit 1 is carried out.

Keywords: Condition-based maintenance, opportunistic maintenance, preventive maintenance, two-unit system.

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Authors: Justyna Rybicka, Ashutosh Tiwari, Shane Enticott

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In the age of automation and computation aiding manufacturing, it is clear that manufacturing systems have become more complex than ever before. Although technological advances provide the capability to gain more value with fewer resources, sometimes utilisation of the manufacturing capabilities available to organisations is difficult to achieve. Flexible manufacturing systems (FMS) provide a unique capability to manufacturing organisations where there is a need for product range diversification by providing line efficiency through production flexibility. This is very valuable in trend driven production set-ups or niche volume production requirements. Although FMS provides flexible and efficient facilities, its optimal set-up is key in achieving production performance. As many variables are interlinked due to the flexibility provided by the FMS, analytical calculations are not always sufficient to predict the FMS’ performance. Simulation modelling is capable of capturing the complexity and constraints associated with FMS. This paper demonstrates how discrete event simulation (DES) can address complexity in an FMS to optimise the production line performance. A case study of an automotive FMS is presented. The DES model demonstrates different configuration options depending on prioritising objectives: utilisation and throughput. Additionally, this paper provides insight into understanding the impact of system set-up constraints on the FMS performance and demonstrates the exploration into the optimal production set-up.

Keywords: Automotive, capacity performance, discrete event simulation, flexible manufacturing system.

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Authors: M. Gomaa Abdoelatef, Robert M. Field, Lee, Yong-Kwan

Abstract:

Growing human population has placed increased demands on water supplies and spurred a heightened interest in desalination infrastructure. Key elements of the economics of desalination projects are thermal and electrical inputs. With growing concerns over use of fossil fuels to (indirectly) supply these inputs, coupling of desalination with nuclear power production represents a significant opportunity. Individually, nuclear and desalination technologies have a long history and are relatively mature. For desalination, Reverse Osmosis (RO) has the lowest energy inputs. However, the economically driven output quality of the water produced using RO, which uses only electrical inputs, is lower than the output water quality from thermal desalination plants. Therefore, modern desalination projects consider that RO should be coupled with thermal desalination technologies (MSF, MED, or MED-TVC) with attendant steam inputs to permit blending to produce various qualities of water. A large nuclear facility is well positioned to dispatch large quantities of both electrical and thermal power. This paper considers the supply of thermal energy to a large desalination facility to examine heat balance impact on the nuclear steam cycle. The APR1400 nuclear plant is selected as prototypical from both a capacity and turbine cycle heat balance perspective to examine steam supply and the impact on electrical output. Extraction points and quantities of steam are considered parametrically along with various types of thermal desalination technologies to form the basis for further evaluations of economically optimal approaches to the interface of nuclear power production with desalination projects. In our study, the thermodynamic evaluation will be executed by DE-TOP, an IAEA sponsored program. DE-TOP has capabilities to analyze power generation systems coupled to desalination plants through various steam extraction positions, taking into consideration the isolation loop between the nuclear and the thermal desalination facilities (i.e., for radiological isolation).

Keywords: APR1400, Cogeneration, Desalination, DE-TOP, IAEA, MED, MED-TVC, MSF, RO.

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Authors: Rahil Garnavi, Mohammad Aldeen, M. Emre Celebi, Alauddin Bhuiyan, Constantinos Dolianitis, George Varigos

Abstract:

Automatic segmentation of skin lesions is the first step towards development of a computer-aided diagnosis of melanoma. Although numerous segmentation methods have been developed, few studies have focused on determining the most discriminative and effective color space for melanoma application. This paper proposes a novel automatic segmentation algorithm using color space analysis and clustering-based histogram thresholding, which is able to determine the optimal color channel for segmentation of skin lesions. To demonstrate the validity of the algorithm, it is tested on a set of 30 high resolution dermoscopy images and a comprehensive evaluation of the results is provided, where borders manually drawn by four dermatologists, are compared to automated borders detected by the proposed algorithm. The evaluation is carried out by applying three previously used metrics of accuracy, sensitivity, and specificity and a new metric of similarity. Through ROC analysis and ranking the metrics, it is shown that the best results are obtained with the X and XoYoR color channels which results in an accuracy of approximately 97%. The proposed method is also compared with two state-ofthe- art skin lesion segmentation methods, which demonstrates the effectiveness and superiority of the proposed segmentation method.

Keywords: Border detection, Color space analysis, Dermoscopy, Histogram thresholding, Melanoma, Segmentation.

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Authors: Rajneesh Sharma, M. Gopal

Abstract:

Markov games are a generalization of Markov decision process to a multi-agent setting. Two-player zero-sum Markov game framework offers an effective platform for designing robust controllers. This paper presents two novel controller design algorithms that use ideas from game-theory literature to produce reliable controllers that are able to maintain performance in presence of noise and parameter variations. A more widely used approach for controller design is the H∞ optimal control, which suffers from high computational demand and at times, may be infeasible. Our approach generates an optimal control policy for the agent (controller) via a simple Linear Program enabling the controller to learn about the unknown environment. The controller is facing an unknown environment, and in our formulation this environment corresponds to the behavior rules of the noise modeled as the opponent. Proposed controller architectures attempt to improve controller reliability by a gradual mixing of algorithmic approaches drawn from the game theory literature and the Minimax-Q Markov game solution approach, in a reinforcement-learning framework. We test the proposed algorithms on a simulated Inverted Pendulum Swing-up task and compare its performance against standard Q learning.

Keywords: Reinforcement learning, Markov Decision Process, Matrix Games, Markov Games, Smooth Fictitious play, Controller, Inverted Pendulum.

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Authors: Fouad Salha , X. Guillaud

Abstract:

Directional over current relays (DOCR) are commonly used in power system protection as a primary protection in distribution and sub-transmission electrical systems and as a secondary protection in transmission systems. Coordination of protective relays is necessary to obtain selective tripping. In this paper, an approach for efficiency reduction of DOCRs nonlinear optimum coordination (OC) is proposed. This was achieved by modifying the objective function and relaxing several constraints depending on the four constraints classification, non-valid, redundant, pre-obtained and valid constraints. According to this classification, the far end fault effect on the objective function and constraints, and in consequently on relay operating time, was studied. The study was carried out, firstly by taking into account the near-end and far-end faults in DOCRs coordination problem formulation; and then faults very close to the primary relays (nearend faults). The optimal coordination (OC) was achieved by simultaneously optimizing all variables (TDS and Ip) in nonlinear environment by using of Genetic algorithm nonlinear programming techniques. The results application of the above two approaches on 6-bus and 26-bus system verify that the far-end faults consideration on OC problem formulation don-t lose the optimality.

Keywords: Backup/Primary relay, Coordination time interval (CTI), directional over current relays, Genetic algorithm, time dial setting (TDS), pickup current setting (Ip), nonlinear programming.

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Authors: D. Moussazadeh, A. Aytug

Abstract:

The focus of this study is to analyze and elaborate the formal factors in the architectural features of the museums. From aesthetic vantage point, this study has scrutinized the formal aesthetic values and identity-related features of the museums. Furthermore, the importance of the museums as the centers of knowledge, science and arts has gradually increased in the last century, whereby they have shifted from an elite standing to the pluralist approach as to address every sections of the community. This study will focus on the museum structures that are designed with the aesthetic apprehension, and presented as the artistic works on the basis of an objective attitude to elaborate the formal aesthetic factors on the formal aesthetics. It is of great importance to increase such studies for getting some concrete results to perceive the recent term aesthetic approaches and improve the forms in line with such approaches. This study elaborates the aesthetic facts solely on the basis of visual dimensions, but ignores the subjective effects to evaluate it in formal, subjective and conceptual aspects. The main material of this study comprises of the descriptive works on the conceptual substructure, and a number of schedules drawn on such concepts, which are applied on the example museum structures. Such works cover many several existing sources such as the design, philosophy, artistic philosophy, shape, form, design elements and principles as well as the museums.

Keywords: Aesthetics, design principles and elements, Gestalt.

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Authors: Chaudhary Itisha, Shankar Manu

Abstract:

Patient satisfaction represents a crucial aspect in the evaluation of health care services. Preoperative teaching provides the patient with pertinent information concerning the surgical process and the intended surgical procedure as well as anticipated patient behavior (anxiety, fear), expected sensation, and the probable outcomes. Although patient education is part of Accreditation protocols, it is not uniform at most places. The aim of this study was to try to assess the benefit of preoperative patient education on selected post-operative outcome parameters; mainly, post-operative pain scores, requirement of additional analgesia, return to activity of daily living and overall patient satisfaction, and try to standardize few education protocols. Dependent variables were measured before and after the treatment on a study population of 302 volunteers. Educational intervention was provided by the Investigator in the preoperative period to the study group through personal counseling. An information booklet contained detailed information was also provided. Statistical Analysis was done using Chi square test, Mann Whitney u test and Fischer Exact Test on a total of 302 subjects. P value <0.05 was considered as level of statistical significance and p<0.01 was considered as highly significant. This study suggested that patients who are given a structured, individualized and elaborate preoperative education and counseling have a better ability to cope up with postoperative pain in the immediate post-operative period. However, there was not much difference when the patients have had almost complete recovery. There was no difference in the requirement of additional analgesia among the two groups. There is a positive effect of preoperative counseling on expected return to the activities of daily living and normal work schedule. However, no effect was observed on the activities in the immediate post-operative period. There is no difference in the overall satisfaction score among the two groups of patients. Thus this study concludes that there is a positive benefit as suggested by the results for pre-operative patient education. Although the difference in various parameters studied might not be significant over a long term basis, they definitely point towards the benefits of preoperative patient education. 

Keywords: Patient education, post-operative pain, patient satisfaction, post-operative outcome.

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Authors: J. Ritonja, R. Brezovnik, M. Petrun, B. Polajžer

Abstract:

Many modern synchronous generators in power systems are extremely weakly damped. The reasons are cost optimization of the machine building and introduction of the additional control equipment into power systems. Oscillations of the synchronous generators and related stability problems of the power systems are harmful and can lead to failures in operation and to damages. The only useful solution to increase damping of the unwanted oscillations represents the implementation of the power system stabilizers. Power system stabilizers generate the additional control signal which changes synchronous generator field excitation voltage. Modern power system stabilizers are integrated into static excitation systems of the synchronous generators. Available commercial power system stabilizers are based on linear control theory. Due to the nonlinear dynamics of the synchronous generator, current stabilizers do not assure optimal damping of the synchronous generator’s oscillations in the entire operating range. For that reason the use of the robust power system stabilizers which are convenient for the entire operating range is reasonable. There are numerous robust techniques applicable for the power system stabilizers. In this paper the use of sliding mode control for synchronous generator stability improvement is studied. On the basis of the sliding mode theory, the robust power system stabilizer was developed. The main advantages of the sliding mode controller are simple realization of the control algorithm, robustness to parameter variations and elimination of disturbances. The advantage of the proposed sliding mode controller against conventional linear controller was tested for damping of the synchronous generator oscillations in the entire operating range. Obtained results show the improved damping in the entire operating range of the synchronous generator and the increase of the power system stability. The proposed study contributes to the progress in the development of the advanced stabilizer, which will replace conventional linear stabilizers and improve damping of the synchronous generators.

Keywords: Control theory, power system stabilizer, robust control, sliding mode control, stability, synchronous generator.

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

Abstract:

Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: Beam structures, layerwise, optimization, variable angle tow, neural network

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